├── .RData ├── .Rhistory ├── .Rproj.user ├── 8A50D253 │ ├── pcs │ │ ├── debug-breakpoints.pper │ │ ├── files-pane.pper │ │ ├── find-in-files.pper │ │ ├── source-pane.pper │ │ ├── windowlayoutstate.pper │ │ └── workbench-pane.pper │ ├── persistent-state │ ├── saved_source_markers │ └── sdb │ │ ├── per │ │ └── t │ │ │ ├── 19F123E4 │ │ │ ├── 1EA5907E │ │ │ ├── 73ECF038 │ │ │ ├── 8C4BD055 │ │ │ ├── 99649CAC │ │ │ ├── BB09661E │ │ │ └── DC23D4FA │ │ └── prop │ │ ├── 11883573 │ │ ├── 32248325 │ │ ├── 68675942 │ │ ├── 76246031 │ │ ├── 140CABDE │ │ ├── 1A44F4FC │ │ ├── 221174BD │ │ ├── 2A33A06D │ │ ├── 2B7E67D0 │ │ ├── 2D28D210 │ │ ├── 2DA6D6B0 │ │ ├── 324CBC30 │ │ ├── 484C7DCC │ │ ├── 4CD40149 │ │ ├── 55670BBE │ │ ├── 58CADEA0 │ │ ├── 5A79CF8F │ │ ├── 5B259621 │ │ ├── 64D64EA9 │ │ ├── 6A9E6961 │ │ ├── 6E8CEFA7 │ │ ├── 70032E9E │ │ ├── 768B1A0D │ │ ├── 7A9F0200 │ │ ├── 841388A5 │ │ ├── 85DB6DF │ │ ├── 886014D2 │ │ ├── 8F94BB1 │ │ ├── 9562DCB │ │ ├── 9C314550 │ │ ├── 9ED58F33 │ │ ├── A8F0FCC4 │ │ ├── AF61ED2 │ │ ├── B4E2F8FC │ │ ├── BC30A869 │ │ ├── C0DB0A75 │ │ ├── C60A2888 │ │ ├── C74D6359 │ │ ├── CB71E45C │ │ ├── E0641EB0 │ │ ├── E2B01BC2 │ │ ├── F011FF8C │ │ ├── F3C2FA9F │ │ ├── F4108B1A │ │ ├── FF338CBA │ │ ├── FFB20693 │ │ └── INDEX └── 93BC151B │ ├── pcs │ ├── files-pane.pper │ ├── find-in-files.pper │ ├── packages-pane.pper │ ├── source-pane.pper │ ├── windowlayoutstate.pper │ └── workbench-pane.pper │ └── sdb │ ├── per │ └── t │ │ ├── 21EBB49B │ │ ├── 3065D9D6 │ │ ├── B26FAB2 │ │ └── D04C3A18 │ └── prop │ ├── 28F6BF01 │ ├── 347565E5 │ ├── 370278D2 │ ├── 554A2E9D │ ├── 69DC04A6 │ ├── 769B8DF6 │ ├── 9A4E8FDC │ ├── B85CA76A │ ├── C08B4901 │ ├── C9B6B2B3 │ ├── D135F4A6 │ ├── D2CF7CAD │ ├── D5E6305E │ ├── F22F3062 │ ├── F35B16BA │ ├── FDC2FC1 │ └── INDEX ├── Chapters ├── 10 │ ├── CHAP.txt │ ├── Chapter10a_LRTs_CIs_Figures.xlsx │ ├── Chapter10b_LRTs_CIs_Figures.xlsx │ ├── OCTO.txt │ ├── SAS_Chapter10a │ │ ├── SAS_Chapter10a.sas7bdat │ │ ├── SAS_Chapter10a_Output.html │ │ ├── SAS_Chapter10a_Syntax.html │ │ └── SAS_Chapter10a_Syntax.sas │ └── SAS_Chapter10b │ │ ├── SAS_Chapter10b.sas7bdat │ │ ├── SAS_Chapter10b_Output.html │ │ └── SAS_Chapter10b_Syntax.sas ├── 11 │ ├── CPE.txt │ ├── Chapter11a_LRTs_CIs_R2.xlsx │ ├── Chapter11b_LRTs_R2.xlsx │ ├── SAS_Chapter11a │ │ ├── SAS_Chapter11a.sas7bdat │ │ ├── SAS_Chapter11a_Output.html │ │ ├── SAS_Chapter11a_Syntax.html │ │ └── SAS_Chapter11a_Syntax.sas │ └── SAS_Chapter11b │ │ ├── SAS_Chapter11b.sas7bdat │ │ ├── SAS_Chapter11b_Output.html │ │ ├── SAS_Chapter11b_Syntax.html │ │ └── SAS_Chapter11b_Syntax.sas ├── 12 │ ├── Chapter12_LRTs_CIs_R2_Figure.xlsx │ └── SAS_Chapter12 │ │ ├── SAS_Chapter12.sas7bdat │ │ ├── SAS_Chapter12_Output.html │ │ ├── SAS_Chapter12_Syntax.html │ │ └── SAS_Chapter12_Syntax.sas ├── 02 │ ├── Chapter2_Regions_Figures.xlsx │ ├── MPLUS_Chapter2 │ │ ├── MPLUS_Chapter2.csv │ │ ├── MPLUS_Chapter2_aEq3_EmptyMeans.inp │ │ ├── MPLUS_Chapter2_aEq3_EmptyMeans.out │ │ ├── MPLUS_Chapter2_bEq4_AddAge85.inp │ │ ├── MPLUS_Chapter2_bEq4_AddAge85.out │ │ ├── MPLUS_Chapter2_cEq4_AddOriginalAge.inp │ │ ├── MPLUS_Chapter2_cEq4_AddOriginalAge.out │ │ ├── MPLUS_Chapter2_dEq6_AddGrip9.inp │ │ ├── MPLUS_Chapter2_dEq6_AddGrip9.out │ │ ├── MPLUS_Chapter2_eEq7_AddSexMW.inp │ │ ├── MPLUS_Chapter2_eEq7_AddSexMW.out │ │ ├── MPLUS_Chapter2_fEq6_AddSexWM.inp │ │ ├── MPLUS_Chapter2_fEq6_AddSexWM.out │ │ ├── MPLUS_Chapter2_gEq8_AddDemNFDemNC.inp │ │ ├── MPLUS_Chapter2_gEq8_AddDemNFDemNC.out │ │ ├── MPLUS_Chapter2_hEq9_AddAge85byGrip9.inp │ │ ├── MPLUS_Chapter2_hEq9_AddAge85byGrip9.out │ │ ├── MPLUS_Chapter2_iEq9_AddAge80byGrip12.inp │ │ ├── MPLUS_Chapter2_iEq9_AddAge80byGrip12.out │ │ ├── MPLUS_Chapter2_jEq9_AddAge90byGrip6.inp │ │ ├── MPLUS_Chapter2_jEq9_AddAge90byGrip6.out │ │ ├── MPLUS_Chapter2_kEq13_AddSexMWbyDemNFNC.inp │ │ ├── MPLUS_Chapter2_kEq13_AddSexMWbyDemNFNC.out │ │ ├── MPLUS_Chapter2_lEq13_AddSexWMbyDemNFNC.inp │ │ ├── MPLUS_Chapter2_lEq13_AddSexWMbyDemNFNC.out │ │ ├── MPLUS_Chapter2_mEq15_AddSexMWbyDemFNFC.inp │ │ ├── MPLUS_Chapter2_mEq15_AddSexMWbyDemFNFC.out │ │ ├── MPLUS_Chapter2_nEq15_AddSexWMbyDemFNFC.inp │ │ ├── MPLUS_Chapter2_nEq15_AddSexWMbyDemFNFC.out │ │ ├── MPLUS_Chapter2_oEq16_AddSexMWbyDemCNCF.inp │ │ ├── MPLUS_Chapter2_oEq16_AddSexMWbyDemCNCF.out │ │ ├── MPLUS_Chapter2_pEq16_AddSexWMbyDemCNCF.inp │ │ ├── MPLUS_Chapter2_pEq16_AddSexWMbyDemCNCF.out │ │ ├── MPLUS_Chapter2_qEq17_AddAgeSexGripSex.inp │ │ ├── MPLUS_Chapter2_qEq17_AddAgeSexGripSex.out │ │ ├── MPLUS_Chapter2_rEq18_AddAgeGripSex.inp │ │ ├── MPLUS_Chapter2_rEq18_AddAgeGripSex.out │ │ ├── MPLUS_Chapter2_sEq13_Final.inp │ │ └── MPLUS_Chapter2_sEq13_Final.out │ ├── OCTO.txt │ ├── R_Chapter2 │ │ ├── dsL.R │ │ ├── hoffman-ch2.R │ │ ├── hoffman-ch2.Rmd │ │ └── hoffman-ch2.html │ ├── SAS_Chapter2 │ │ ├── SAS_Chapter2.sas7bdat │ │ ├── SAS_Chapter2_Output.html │ │ ├── SAS_Chapter2_Syntax.html │ │ └── SAS_Chapter2_Syntax.sas │ └── hoffman-ch2.knit.md ├── 03 │ ├── CHAP.txt │ ├── Chapter3b_LRTs.xlsx │ ├── MPLUS_Chapter3a │ │ ├── MPLUS_Chapter3a.csv │ │ ├── MPLUS_Chapter3a_aEq1_EmptyBPModel.inp │ │ ├── MPLUS_Chapter3a_aEq1_EmptyBPModel.out │ │ ├── MPLUS_Chapter3a_bEq2_EmptyWPModel.inp │ │ ├── MPLUS_Chapter3a_bEq2_EmptyWPModel.out │ │ ├── MPLUS_Chapter3a_cEq7_CondBPModel.inp │ │ ├── MPLUS_Chapter3a_cEq7_CondBPModel.out │ │ ├── MPLUS_Chapter3a_dEq7_CondWPModel.inp │ │ └── MPLUS_Chapter3a_dEq7_CondWPModel.out │ ├── MPLUS_Chapter3b │ │ ├── MPLUS_Chapter3b.csv │ │ ├── MPLUS_Chapter3b_aEq10_BPANOVA.inp │ │ ├── MPLUS_Chapter3b_aEq10_BPANOVA.out │ │ ├── MPLUS_Chapter3b_bEq10_UnivRMANOVA.inp │ │ ├── MPLUS_Chapter3b_bEq10_UnivRMANOVA.out │ │ ├── MPLUS_Chapter3b_cEq10_MultivRMANOVA.inp │ │ └── MPLUS_Chapter3b_cEq10_MultivRMANOVA.out │ ├── R_Chapter3 │ │ ├── figure_rmd │ │ │ ├── EmptyBP4.png │ │ │ ├── EmptyBP5.png │ │ │ ├── EmptyWP4.png │ │ │ ├── EmptyWP5.png │ │ │ ├── GraphingData0.png │ │ │ ├── GraphingData1.png │ │ │ ├── GraphingData2.png │ │ │ ├── GraphingData3.png │ │ │ └── StackData.png │ │ ├── hoffman-ch3.R │ │ ├── hoffman-ch3.Rmd │ │ ├── hoffman-ch3.html │ │ └── slide308.R │ ├── SAS_Chapter3a │ │ ├── SAS_Chapter3a.sas7bdat │ │ ├── SAS_Chapter3a_Output.html │ │ ├── SAS_Chapter3a_Syntax.html │ │ └── SAS_Chapter3a_Syntax.sas │ └── SAS_Chapter3b │ │ ├── SAS_Chapter3b.sas7bdat │ │ ├── SAS_Chapter3b_Output.html │ │ ├── SAS_Chapter3b_Syntax.html │ │ └── SAS_Chapter3b_Syntax.sas ├── 04 │ ├── Chapter4_LRTs.xlsx │ ├── MIDUS-NSDE.txt │ └── SAS_Chapter4 │ │ ├── SAS_Chapter4.sas7bdat │ │ ├── SAS_Chapter4_Output.html │ │ ├── SAS_Chapter4_Syntax.html │ │ └── SAS_Chapter4_Syntax.sas ├── 05 │ ├── Chapter5_LRTs_CIs_R2.xlsx │ ├── MPlus_Chapter5 │ │ ├── Ch5_Mplus.pdf │ │ ├── ELSA_LONG_n1000.dat │ │ ├── ELSA_MLMGROWTH_EMPTY.inp │ │ └── elsa_mlmgrowth_empty.out │ ├── R_Chapter5 │ │ ├── .Rhistory │ │ ├── SimpleExample_Key.R │ │ ├── SimpleExample_Key.xlsx │ │ ├── SimpleExample_studentCopy.R │ │ ├── SimpleExample_studentCopy.xlsx │ │ ├── ch5-ELSA.R │ │ ├── ch5-ELSA.Rmd │ │ ├── ch5-ELSA.html │ │ ├── figure_rmd │ │ │ ├── GraphM3_1.png │ │ │ ├── GraphM5_1.png │ │ │ ├── GraphM5_3.png │ │ │ ├── GraphM5_5.png │ │ │ ├── GraphingData0.png │ │ │ ├── GraphingData1.png │ │ │ └── GraphingData2.png │ │ ├── general.JPG │ │ ├── hoffman-ch5.R │ │ ├── hoffman-ch5.Rmd │ │ ├── hoffman-ch5.html │ │ ├── how to adapt CH5 script for ELSA study.txt │ │ └── images │ │ │ ├── general.JPG │ │ │ ├── m3.1.JPG │ │ │ ├── m5.1.JPG │ │ │ ├── m5.3.JPG │ │ │ ├── m5.5.JPG │ │ │ └── m5.5a.JPG │ └── SAS_Chapter5 │ │ ├── SAS_Chapter5.sas7bdat │ │ ├── SAS_Chapter5_Output.html │ │ ├── SAS_Chapter5_Syntax.html │ │ └── SAS_Chapter5_Syntax.sas ├── 06 │ ├── CHAP.txt │ ├── Chapter6_LRTs_CIs_R2.xlsx │ ├── MPlus_Chpater6 │ │ ├── 2b R(I) R(S).inp │ │ ├── 2b r(i) r(s).out │ │ ├── 3A R(I) R(S) F(Q).inp │ │ ├── 3a r(i) r(s) f(q).out │ │ ├── MPLUS_Chapter6.csv │ │ └── MPLUS_Chpater6 (1).csv │ └── SAS_Chapter6 │ │ ├── SAS_Chapter6.sas7bdat │ │ ├── SAS_Chapter6_Output.html │ │ ├── SAS_Chapter6_Syntax.html │ │ └── SAS_Chapter6_Syntax.sas ├── 07 │ ├── CHAP.txt │ ├── Chapter7a_LRTs_CIs_R2_Regions.xlsx │ ├── Chapter7b_LRTs_CIs_R2_Figure.xlsx │ ├── FRP.txt │ ├── SAS_Chapter7a │ │ ├── SAS_Chapter7a.sas7bdat │ │ ├── SAS_Chapter7a_Output.html │ │ ├── SAS_Chapter7a_Syntax.html │ │ └── SAS_Chapter7a_Syntax.sas │ └── SAS_Chapter7b │ │ ├── SAS_Chapter7b.sas7bdat │ │ ├── SAS_Chapter7b_Output.html │ │ ├── SAS_Chapter7b_Syntax.html │ │ └── SAS_Chapter7b_Syntax.sas ├── 08 │ ├── CHAP.txt │ ├── Chapter8_LRTs_CIs_R2_Figures.xlsx │ └── SAS_Chapter8 │ │ ├── SAS_Chapter8.sas7bdat │ │ ├── SAS_Chapter8_Output.html │ │ ├── SAS_Chapter8_Syntax.html │ │ └── SAS_Chapter8_Syntax.sas └── 09 │ ├── Chapter9_LRTs_CIs_R2.xlsx │ ├── FRP.txt │ └── SAS_Chapter9 │ ├── SAS_Chapter9.sas7bdat │ ├── SAS_Chapter9_Output.html │ ├── SAS_Chapter9_Syntax.html │ └── SAS_Chapter9_Syntax.sas ├── Data ├── Derived │ ├── ELSA │ │ └── dsL_ELSA.rds │ └── MPLUS_Chpater6.csv └── Raw │ ├── ELSA │ ├── ds0_ELSA.rds │ └── dsELSA.rds │ └── HRS │ └── HRS_WIDE_n2000.dat ├── Projects ├── ELSA │ └── CogDecline │ │ ├── ELSA_report.Rmd │ │ ├── ELSA_report.html │ │ ├── dsELSA.R │ │ ├── dsL_ELSA.csv │ │ ├── dsL_ELSA.dat │ │ ├── dsL_ELSA_varNames.csv │ │ ├── dsW_ELSA.dat │ │ ├── dsW_ELSA_varNames.csv │ │ ├── extract from mplus.R │ │ ├── figure_rmd │ │ ├── BasicLinePlot-1.png │ │ ├── CrossSectionCount-1.png │ │ ├── CrossSectionDist-1.png │ │ ├── IndividualPredictionsAge-1.png │ │ ├── IndividualPredictionsAge2-1.png │ │ ├── ProtoLines-1.png │ │ └── ProtoLines2-1.png │ │ └── irecall │ │ ├── dsL_ELSA.csv │ │ ├── irecall_r(I)_r(S)_(IS)Age80.inp │ │ ├── irecall_r(I)_r(S)_(IS)Age80_(IS)Edu11.inp │ │ ├── irecall_r(I)_r(S)_(IS)Age80_(IS)Edu11_(IS)Smoked.inp │ │ ├── irecall_r(I)_r(S)_NoCovar.inp │ │ ├── irecall_r(i)_r(s)_(is)age80.gh5 │ │ ├── irecall_r(i)_r(s)_(is)age80.out │ │ ├── irecall_r(i)_r(s)_(is)age80_(is)edu11.gh5 │ │ ├── irecall_r(i)_r(s)_(is)age80_(is)edu11.out │ │ ├── irecall_r(i)_r(s)_(is)age80_(is)edu11_(is)smoked.gh5 │ │ ├── irecall_r(i)_r(s)_(is)age80_(is)edu11_(is)smoked.out │ │ ├── irecall_r(i)_r(s)_nocovar.gh5 │ │ ├── irecall_r(i)_r(s)_nocovar.out │ │ ├── results.dat │ │ └── retired │ │ ├── irecall_0r_1f_2x_x.inp │ │ ├── irecall_r0_f1_x2_x.out │ │ ├── irecall_r0_r1_f2_x.inp │ │ ├── irecall_r0_r1_f2_x.out │ │ ├── irecall_r0_r1_r2_012age80.inp │ │ ├── irecall_r0_r1_r2_012age80.out │ │ ├── irecall_r0_r1_r2_012age80_0edu11.inp │ │ ├── irecall_r0_r1_r2_012age80_0edu11.out │ │ ├── irecall_r0_r1_r2_01age80.inp │ │ ├── irecall_r0_r1_r2_01age80.out │ │ ├── irecall_r0_r1_r2_0age80.inp │ │ ├── irecall_r0_r1_r2_0age80.out │ │ ├── irecall_r0_r1_r2_age012.inp │ │ ├── irecall_r0_r1_r2_age012.out │ │ ├── irecall_r0_r1_r2_x.inp │ │ ├── irecall_r0_r1_r2_x.out │ │ ├── irecall_r0_r1_x2_x.inp │ │ ├── irecall_r0_r1_x2_x.out │ │ ├── irecall_r0_x1_x2_x.inp │ │ └── irecall_r0_x1_x2_x.out ├── HRS │ ├── HRS.zip │ └── Various │ │ ├── HRS_BASIC.inp │ │ ├── HRS_General Information.docx │ │ ├── HRS_General_VariableList.xlsx │ │ ├── HRS_LGMGROWTH.inp │ │ ├── HRS_LGMGROWTH_ExampWriteup.docx │ │ ├── HRS_LGMGROWTH_age.inp │ │ ├── HRS_LGMGROWTH_piecewise.inp │ │ ├── HRS_LGMGROWTH_timestudy.inp │ │ ├── HRS_MLMGROWTH_WIDETOLONG.inp │ │ ├── HRS_WIDE_n2000.dat │ │ ├── dsHRS.R │ │ ├── hrs_basic.dgm │ │ ├── hrs_basic.gh5 │ │ ├── hrs_basic.out │ │ ├── hrs_lgmgrowth.dgm │ │ ├── hrs_lgmgrowth.gh5 │ │ ├── hrs_lgmgrowth.out │ │ └── namesare.txt ├── LMG_Mplus_primer.pdf └── README.md ├── README.md ├── Scripts ├── Data │ ├── LabelingFactorLevels.R │ ├── dsL.R │ └── loadChapterDatasets.R ├── Graphs │ ├── AesDefine.R │ ├── basicTrajectory.R │ ├── basicTrajectory300.R │ ├── graphThemes.R │ └── line_graph_trajectories.R ├── MPlus │ └── mplus.R └── Utility │ ├── InstallPackages.R │ ├── runAll.R │ ├── runMany.R │ └── runOne.R ├── final ├── Data │ ├── HRS_WIDE_n2000.dat │ └── namesare.txt ├── Documentation │ ├── HRS_General Information.docx │ ├── HRS_General_VariableList.xlsx │ └── HRS_LGMGROWTH_ExampWriteup.docx ├── Mplus │ ├── HRS_BASIC.inp │ ├── HRS_LGMGROWTH.inp │ ├── HRS_LGMGROWTH_age.inp │ ├── HRS_LGMGROWTH_piecewise.inp │ ├── HRS_LGMGROWTH_timestudy.inp │ └── HRS_MLMGROWTH_WIDETOLONG.inp └── README.md ├── general.JPG ├── gradesGraph.R ├── libs └── css │ └── sidebar.css └── psy564.Rproj /.RData: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/.RData -------------------------------------------------------------------------------- /.Rproj.user/8A50D253/pcs/debug-breakpoints.pper: -------------------------------------------------------------------------------- 1 | { 2 | "debugBreakpointsState" : { 3 | "breakpoints" : [ 4 | ] 5 | } 6 | } -------------------------------------------------------------------------------- /.Rproj.user/8A50D253/pcs/files-pane.pper: -------------------------------------------------------------------------------- 1 | { 2 | "path" : "~/GitHub/psy564", 3 | "sortOrder" : [ 4 | { 5 | "ascending" : true, 6 | "columnIndex" : 2 7 | }, 8 | { 9 | "ascending" : true, 10 | "columnIndex" : 1 11 | } 12 | ] 13 | } -------------------------------------------------------------------------------- /.Rproj.user/8A50D253/pcs/find-in-files.pper: -------------------------------------------------------------------------------- 1 | { 2 | "dialog-state" : { 3 | "caseSensitive" : false, 4 | "filePatterns" : [ 5 | ], 6 | "path" : "~/GitHub/psy564", 7 | "query" : "lme4 package", 8 | "regex" : false 9 | } 10 | } -------------------------------------------------------------------------------- /.Rproj.user/8A50D253/pcs/source-pane.pper: -------------------------------------------------------------------------------- 1 | { 2 | "activeTab" : 6 3 | } -------------------------------------------------------------------------------- /.Rproj.user/8A50D253/pcs/windowlayoutstate.pper: -------------------------------------------------------------------------------- 1 | { 2 | "left" : { 3 | "panelheight" : 958, 4 | "splitterpos" : 391, 5 | "topwindowstate" : "MAXIMIZE", 6 | "windowheight" : 996 7 | }, 8 | "right" : { 9 | "panelheight" : 958, 10 | "splitterpos" : 689, 11 | "topwindowstate" : "NORMAL", 12 | "windowheight" : 996 13 | } 14 | } -------------------------------------------------------------------------------- /.Rproj.user/8A50D253/pcs/workbench-pane.pper: -------------------------------------------------------------------------------- 1 | { 2 | "TabSet1" : 1, 3 | "TabSet2" : 0 4 | } -------------------------------------------------------------------------------- /.Rproj.user/8A50D253/persistent-state: -------------------------------------------------------------------------------- 1 | build-last-errors="[]" 2 | build-last-errors-base-dir="" 3 | build-last-outputs="[]" 4 | compile_pdf_state="{\"errors\":[],\"output\":\"\",\"running\":false,\"tab_visible\":false,\"target_file\":\"\"}" 5 | console_procs="[]" 6 | files.monitored-path="" 7 | find-in-files-state="{\"handle\":\"\",\"input\":\"\",\"path\":\"\",\"regex\":true,\"results\":{\"file\":[],\"line\":[],\"lineValue\":[],\"matchOff\":[],\"matchOn\":[]},\"running\":false}" 8 | imageDirtyState="1" 9 | saveActionState="-1" 10 | -------------------------------------------------------------------------------- /.Rproj.user/8A50D253/saved_source_markers: -------------------------------------------------------------------------------- 1 | {"active_set":"","sets":[]} -------------------------------------------------------------------------------- /.Rproj.user/8A50D253/sdb/per/t/19F123E4: -------------------------------------------------------------------------------- 1 | { 2 | "contents" : "# remove all elements for a clean start\nrm(list=ls(all=TRUE))\ncat(\"\\014\")\n\n\n## @knitr InstallPackage\n# source(\"./Scripts/Utility/InstallPackages.R\")\n\n\n\n## @knitr LoadPackages\nrequire(sas7bdat) # for inputting data \nlibrary(dplyr) # for general data manipulation\n# library(reshape2) # for data : wide <-> long\n# library(psych) # data summary + etc\nlibrary(ggplot2) # graphing\n# library(nlme) # estimate fixed models | esp. gls()\n# library(lme4) # estimate mixed models | esp. lmer()\n# library(arm) # process model objects\n\n\n## @knitr LoadData\nds0 <- read.csv(\"~/GitHub/psy564/Data/Raw/HRS/HRS_WIDE_n2000.dat\", header=F)\ndim(ds0)\n\n# namesare <- read.table(\"./Projects/HRS/HRS/namesare.txt\", sep=\" \")\nnamesarePath <- \"./Projects/HRS/Various/namesare.txt\"\nnamesare <- scan (namesarePath, what=\"character\", sep=\" \")\nnames(ds0) <- namesare\n\nselectVars <- c()", 3 | "created" : 1426623137609.000, 4 | "dirty" : false, 5 | "encoding" : "UTF-8", 6 | "folds" : "", 7 | "hash" : "4013783609", 8 | "id" : "19F123E4", 9 | "lastKnownWriteTime" : 1427776920, 10 | "path" : "~/GitHub/psy564/Projects/HRS/Various/dsHRS.R", 11 | "project_path" : "Projects/HRS/Various/dsHRS.R", 12 | "properties" : { 13 | }, 14 | "relative_order" : 0, 15 | "source_on_save" : false, 16 | "type" : "r_source" 17 | } -------------------------------------------------------------------------------- /.Rproj.user/8A50D253/sdb/per/t/73ECF038: -------------------------------------------------------------------------------- 1 | { 2 | "contents" : "# remove all elements for a clean start\nrm(list=ls(all=TRUE))\ncat(\"\\014\")\n\n## @knitr LoadPackages\nrequire(sas7bdat) # for inputting data \nlibrary(dplyr) # for general data manipulation\nlibrary(reshape2) # for data : wide <-> long\nlibrary(psych) # data summary + etc\nlibrary(ggplot2) # graphing\nlibrary(nlme) # estimate fixed models | esp. gls()\nlibrary(lme4) # estimate mixed models | esp. lmer()\nlibrary(arm) # process model objects\n\n# source(\"./Scripts/Mplus/mplus.R\")\nsource(\"http://www.statmodel.com/mplus-R/mplus.R\")\nls() # list the availible function in mplus.R\n\nm0 <- \"./Projects/ELSA/CogDecline/irecall/irecall_r(i)_r(s)_nocovar.gh5\"\nm1 <- \"./Projects/ELSA/CogDecline/irecall/irecall_r(i)_r(s)_(is)age80.gh5\"\nm2 <- \"./Projects/ELSA/CogDecline/irecall/irecall_r(i)_r(s)_(is)age80_(is)edu11.gh5\"\nm3 <- \"./Projects/ELSA/CogDecline/irecall/irecall_r(i)_r(s)_(is)age80_(is)edu11_(is)smoked.gh5\"\n\n\nmplus.view.plots(m3)\nmodel <- m3\n\nmplus.list.variables(m3)\n\nmplus.plot.histogram(model, \"OUTCOME\")\nmplus.plot.histogram(model, \"TIMEL\")\nmplus.plot.histogram(model, \"EVRSMK1A\")\nmplus.plot.histogram(model, \"EDU11\")\nmplus.plot.histogram(model, \"AGE80\")\nmplus.plot.histogram(model, \"LINEAR\")\nmplus.plot.histogram(model, \"B_OUTCOME\")\n\n# extract raw data\na <- mplus.get.data(m2,\"OUTCOME\")\nb <- mplus.get.data(m2,\"TIMEL\")\nc <- mplus.get.data(m2,\"EDU11\")\nd <- mplus.get.data(m2,\"AGE80\")\ne <- mplus.get.data(m2,\"LINEAR\")\nf <- mplus.get.data(m2,\"B_OUTCOME\")\ng <- mplus.get.data(m2,\"ID\")\n\nds <- data.frame(cbind(a, b, c, d, e, f, g))\nnames(ds) <- c(\"OUTCOME\", \"TIMEL\",\"EDU11\",\"AGE80\",\"LINEAR\",\"B_OUTCOME\",\"ID\")\n\nhead(ds)\n\n\n\n###### ########\nmplus.load(m1)\nmplus.plot.loop(m1, ypred)\n\nsource(\"http://www.statmodel.com/mplus-R/mplus.R\")\nls() # list the availible function in mplus.R\n\n# create objects containing the paths to gh5 files\nmodel_basic <- './Projects/HRS/Various/HRS_BASIC.gh5'\nmodel_growth <- './Projects/HRS/Various/hrs_lgmgrowth.gh5'\n\n# choose what model to work with\nmodel <- model_basic\nmodel <- model_growth\n\n\nmplus.list.variables(model)\nmplus.plot.histogram(model,'CDWR1')\nmplus.plot.histogram(model,'I')\nmplus.plot.histogram(model,'S')\n\nmplus.plot.loop(model)\n\nmplus.plot.scatterplot('HRS_BASIC.gh5','CDWRSCR4','DAGEYRS4')\n\n\n\n\n", 3 | "created" : 1428010904751.000, 4 | "dirty" : false, 5 | "encoding" : "UTF-8", 6 | "folds" : "", 7 | "hash" : "911814083", 8 | "id" : "73ECF038", 9 | "lastKnownWriteTime" : 1427776920, 10 | "path" : "~/GitHub/psy564/Projects/ELSA/CogDecline/extract from mplus.R", 11 | "project_path" : "Projects/ELSA/CogDecline/extract from mplus.R", 12 | "properties" : { 13 | }, 14 | "relative_order" : 0, 15 | "source_on_save" : false, 16 | "type" : "r_source" 17 | } -------------------------------------------------------------------------------- /.Rproj.user/8A50D253/sdb/per/t/BB09661E: -------------------------------------------------------------------------------- 1 | { 2 | "contents" : "---\ntitle: \"Reporting Statistical Models (demo)\"\nauthor: \"Psyc 564\"\ndate: \"Friday, January 30, 2015\"\noutput:\n html_document:\n css: ~/GitHub/psy564/libs/css/sidebar.css\n highlight: haddock\n theme: spacelab\n toc: yes\n---\n\n\n```{r, echo=F, message=F} \nlibrary(knitr)\nopts_knit$set(root.dir='../../../') #Don't combine this call with any other chunk -especially one that uses file paths.\n```\n\n\n```{r, echo=F, message=T}\nrequire(knitr)\nopts_chunk$set(\n results='show', \n message = TRUE,\n comment = NA, \n tidy = FALSE,\n# fig.height = 4.8, \n# fig.width = 6.5, \n out.width = NULL,\n fig.path = 'figure_rmd/', \n dev = \"png\",\n dpi = 70\n)\nechoChunks <- FALSE\nwarningChunks<- FALSE\nmessageChunks<- FALSE\noutwidthChunks <- \"130%\"\noptions(width=120) #So the output is 50% wider than the default.\nread_chunk(\"./Projects/ELSA/CogDecline/dsELSA.R\") # the file to which knitr calls for the chunks\n```\n\n## LoadPackages\n```{r LoadPackages}\n\n```\n\n\n## Load data\n```{r LoadData}\n\n```\n\n\n## DataFilter\n```{r DataFilter}\n\n```\n\n\n## DataFilter2\n```{r DataFilter2}\n\n```\n\n## DataExportLong\n```{r DataExportLong, eval=F}\n\n```\n\n## DataExportWide\n```{r DataExportWide, eval=F,echo=F}\n\n```\nNOTE: the export of the wide data is suppressed for brevity\n\n## LoadGraphThemes\n```{r LoadGraphThemes}\n\n```\n\n## CrossSectionDist\n```{r CrossSectionDist, out.width=\"900px\"}\n\n```\n\n## CrossSectionCount\n```{r CrossSectionCount, out.width=\"900px\"}\n\n```\n\n## MakeAgeBins\n```{r MakeAgeBins}\n\n```\n\n## EasyData\n```{r EasyData}\n\n```\n\n## BasicLinePlot\n```{r BasicLinePlot, warning=F,out.width=\"900px\"}\n\n```\n\n## DefineModelData\n```{r DefineModelData, warning=F}\n\n```\n\n## ProtoLines\n```{r ProtoLines, warning=F}\n\n```\n\n## IndividualPredictionsAge\n```{r IndividualPredictionsAge, warning=F, out.width=\"900px\"}\n\n```\n\n\n\n## DefineModelData2\n```{r DefineModelData2, warning=F}\n\n```\n\n## ProtoLines2\n```{r ProtoLines2, warning=F}\n\n```\n\n## IndividualPredictionsAge2\n```{r IndividualPredictionsAge2, warning=F}\n\n```\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n\n \n \n", 3 | "created" : 1428009850748.000, 4 | "dirty" : false, 5 | "encoding" : "UTF-8", 6 | "folds" : "", 7 | "hash" : "1121424642", 8 | "id" : "BB09661E", 9 | "lastKnownWriteTime" : 1427776920, 10 | "path" : "~/GitHub/psy564/Projects/ELSA/CogDecline/ELSA_report.Rmd", 11 | "project_path" : "Projects/ELSA/CogDecline/ELSA_report.Rmd", 12 | "properties" : { 13 | }, 14 | "relative_order" : 0, 15 | "source_on_save" : false, 16 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: "# p <- ggplot2::ggplot(dsM,aes(x=time,y=attend, group=id))\n# p <- p + geom_line() \n# p <- p + geom_point(pch=20, size=2.5)\n# p <- p + plotTheme\n# p <- p + scale_x_continuous(limits=c(0,11),\n# breaks=c(0:11))\n# p <- p + scale_y_continuous(limits=c(1,8), \n# breaks=seq(1,8, by=1))\n# p <- p + labs(list(\n# title=\"How often did you attend worship last year?\",\n# x=\"Time scale: years since 2000\", y=\"Church attendance\"))\n\n\n# dsM <- dplyr::filter(dsL, id <=300, \n# raceF != \"Mixed (Non-H)\") %>% \n# dplyr::select(id,sexF,raceF,year,attend,attendF) %>%\n# dplyr::mutate(yearc = year - 2000)\n# \np <- ggplot2::ggplot(dsM,aes(x=time,y=attend))\np <- p + geom_line(aes(group=id), color='firebrick',\n alpha=.2,\n position=position_jitter(w=0.3, h=0.3))\np <- p + geom_point(shape=1, color=\"black\", fill=NA, \n alpha=.4, size=2, \n position=position_jitter(w=0.3, h=0.3))\np <- p + plotTheme\np <- p + scale_x_continuous(limits=c(0,11),\n breaks=c(0:11))\np <- p + scale_y_continuous(limits=c(0,8), \n breaks=seq(1,8, by=1))\np <- p + labs(list(\n title=\"How often did you attend worship last year?\",\n x=\"Time scale: years since 2000\", y=\"Church attendance\"))\np\n", 3 | "created" : 1426265100156.000, 4 | "dirty" : false, 5 | "encoding" : "UTF-8", 6 | "folds" : "", 7 | "hash" : "3582181915", 8 | "id" : "21EBB49B", 9 | "lastKnownWriteTime" : 1425589641, 10 | "path" : "~/GitHub/psy564/Scripts/Graphs/basicTrajectory300.R", 11 | "project_path" : "Scripts/Graphs/basicTrajectory300.R", 12 | "properties" : { 13 | }, 14 | "source_on_save" : false, 15 | "type" : "r_source" 16 | } -------------------------------------------------------------------------------- /.Rproj.user/93BC151B/sdb/per/t/3065D9D6: -------------------------------------------------------------------------------- 1 | { 2 | "contents" : "p <- ggplot2::ggplot(dsM,aes(x=time,y=attend, group=id))\np <- p + geom_line() \np <- p + geom_point(pch=20, size=2.5)\np <- p + plotTheme\np <- p + scale_x_continuous(limits=c(0,11),\n breaks=c(0:11))\np <- p + scale_y_continuous(limits=c(0,8), \n breaks=seq(1,8, by=1))\np <- p + labs(list(\n title=\"How often did you attend worship last year?\",\n x=\"Time scale: years since 2000\", y=\"Church attendance\"))\n", 3 | "created" : 1426265113865.000, 4 | "dirty" : false, 5 | "encoding" : "UTF-8", 6 | "folds" : "", 7 | "hash" : "3428172300", 8 | "id" : "3065D9D6", 9 | "lastKnownWriteTime" : 1425589641, 10 | "path" : "~/GitHub/psy564/Scripts/Graphs/basicTrajectory.R", 11 | "project_path" : "Scripts/Graphs/basicTrajectory.R", 12 | "properties" : { 13 | }, 14 | "source_on_save" : false, 15 | "type" : "r_source" 16 | } -------------------------------------------------------------------------------- /.Rproj.user/93BC151B/sdb/per/t/D04C3A18: -------------------------------------------------------------------------------- 1 | { 2 | "contents" : "# remove all elements for a clean start\nrm(list=ls(all=TRUE))\ncat(\"\\014\")\n\n## @knitr LoadPackages\nrequire(sas7bdat) # for inputting data \nlibrary(dplyr) # for general data manipulation\nlibrary(reshape2) # for data : wide <-> long\nlibrary(psych) # data summary + etc\nlibrary(ggplot2) # graphing\nlibrary(nlme) # estimate fixed models | esp. gls()\nlibrary(lme4) # estimate mixed models | esp. lmer()\nlibrary(arm) # process model objects\n\n# source(\"./Scripts/Mplus/mplus.R\")\nsource(\"http://www.statmodel.com/mplus-R/mplus.R\")\nls() # list the availible function in mplus.R\n\nm0 <- \"./Projects/ELSA/CogDecline/irecall/irecall_r(i)_r(s)_nocovar.gh5\"\nm1 <- \"./Projects/ELSA/CogDecline/irecall/irecall_r(i)_r(s)_(is)age80.gh5\"\nm2 <- \"./Projects/ELSA/CogDecline/irecall/irecall_r(i)_r(s)_(is)age80_(is)edu11.gh5\"\nm3 <- \"./Projects/ELSA/CogDecline/irecall/irecall_r(i)_r(s)_(is)age80_(is)edu11_(is)smoked.gh5\"\n\n\nmplus.view.plots(m3)\nmodel <- m3\n\nmplus.list.variables(m3)\n\nmplus.plot.histogram(model, \"OUTCOME\")\nmplus.plot.histogram(model, \"TIMEL\")\nmplus.plot.histogram(model, \"EVRSMK1A\")\nmplus.plot.histogram(model, \"EDU11\")\nmplus.plot.histogram(model, \"AGE80\")\nmplus.plot.histogram(model, \"LINEAR\")\nmplus.plot.histogram(model, \"B_OUTCOME\")\n\n# extract raw data\na <- mplus.get.data(m2,\"OUTCOME\")\nb <- mplus.get.data(m2,\"TIMEL\")\nc <- mplus.get.data(m2,\"EDU11\")\nd <- mplus.get.data(m2,\"AGE80\")\ne <- mplus.get.data(m2,\"LINEAR\")\nf <- mplus.get.data(m2,\"B_OUTCOME\")\ng <- mplus.get.data(m2,\"ID\")\n\nds <- data.frame(cbind(a, b, c, d, e, f, g))\nnames(ds) <- c(\"OUTCOME\", \"TIMEL\",\"EDU11\",\"AGE80\",\"LINEAR\",\"B_OUTCOME\",\"ID\")\n\nhead(ds)\n\n\n\n###### ########\nmplus.load(m1)\nmplus.plot.loop(m1, ypred)\n\n\n\n", 3 | "created" : 1426028012622.000, 4 | "dirty" : false, 5 | "encoding" : "UTF-8", 6 | "folds" : "", 7 | "hash" : "76570768", 8 | "id" : "D04C3A18", 9 | "lastKnownWriteTime" : 1426274067, 10 | "path" : "~/GitHub/psy564/Projects/ELSA/CogDecline/extract from mplus.R", 11 | "project_path" : "Projects/ELSA/CogDecline/extract from mplus.R", 12 | "properties" : { 13 | "tempName" : "Untitled1" 14 | }, 15 | "source_on_save" : false, 16 | "type" : "r_source" 17 | } -------------------------------------------------------------------------------- /.Rproj.user/93BC151B/sdb/prop/28F6BF01: -------------------------------------------------------------------------------- 1 | { 2 | "tempName" : "Untitled1" 3 | } -------------------------------------------------------------------------------- /.Rproj.user/93BC151B/sdb/prop/347565E5: -------------------------------------------------------------------------------- 1 | { 2 | } -------------------------------------------------------------------------------- /.Rproj.user/93BC151B/sdb/prop/370278D2: -------------------------------------------------------------------------------- 1 | { 2 | } -------------------------------------------------------------------------------- /.Rproj.user/93BC151B/sdb/prop/554A2E9D: 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~%2FGitHub%2FDiabetes-Tri-Study%2FScripts%2FData%2FdsL_ELSA.r="769B8DF6" 2 | ~%2FGitHub%2Fpsy564%2FChapters%2F02%2FR_Chapter2%2Fhoffman-ch2.R="D2CF7CAD" 3 | ~%2FGitHub%2Fpsy564%2FChapters%2F03%2FR_Chapter3%2Fhoffman-ch3.R="69DC04A6" 4 | ~%2FGitHub%2Fpsy564%2FChapters%2F05%2FR_Chapter5%2Fch5-ELSA.R="B85CA76A" 5 | ~%2FGitHub%2Fpsy564%2FChapters%2F05%2FR_Chapter5%2Fch5-ELSA.Rmd="370278D2" 6 | ~%2FGitHub%2Fpsy564%2FChapters%2F05%2FR_Chapter5%2FdsELSA.R="C08B4901" 7 | ~%2FGitHub%2Fpsy564%2FData%2FDerived%2FELSA%2FdsM_ELSA_varNames.csv="FDC2FC1" 8 | ~%2FGitHub%2Fpsy564%2FData%2FDerived%2FELSA%2FdsM_ELSA_varNames.dat="554A2E9D" 9 | ~%2FGitHub%2Fpsy564%2FProjects%2FELSA%2FCogDecline%2FdsELSA.R="347565E5" 10 | ~%2FGitHub%2Fpsy564%2FProjects%2FELSA%2FCogDecline%2Fextract%20from%20mplus.R="28F6BF01" 11 | ~%2FGitHub%2Fpsy564%2FScripts%2FData%2FdsL.R="F35B16BA" 12 | ~%2FGitHub%2Fpsy564%2FScripts%2FData%2FloadChapterDatasets.R="D135F4A6" 13 | ~%2FGitHub%2Fpsy564%2FScripts%2FGraphs%2FbasicTrajectory.R="9A4E8FDC" 14 | ~%2FGitHub%2Fpsy564%2FScripts%2FGraphs%2FbasicTrajectory300.R="D5E6305E" 15 | ~%2FGitHub%2Fpsy564%2FScripts%2FMPlus%2Fmplus.R="C9B6B2B3" 16 | ~%2FGitHub%2Fpsy564%2FScripts%2FUtility%2FInstallPackages.R="F22F3062" 17 | -------------------------------------------------------------------------------- /Chapters/02/Chapter2_Regions_Figures.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Chapters/02/Chapter2_Regions_Figures.xlsx -------------------------------------------------------------------------------- /Chapters/02/MPLUS_Chapter2/MPLUS_Chapter2_aEq3_EmptyMeans.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 2.3: Empty Means Model 3 | 4 | DATA: 5 | FILE = MPLUS_Chapter2.csv; 6 | FORMAT = FREE; 7 | 8 | VARIABLE: 9 | NAMES = PersonID cog age grip sexMW demgroup; 10 | USEVARIABLES = cog; 11 | MISSING = ALL (-9999); 12 | 13 | ANALYSIS: 14 | ESTIMATOR = ML; 15 | PROCESSORS = 4; 16 | 17 | MODEL: 18 | -------------------------------------------------------------------------------- /Chapters/02/MPLUS_Chapter2/MPLUS_Chapter2_bEq4_AddAge85.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 2.4: Adding Age (0=85) 3 | 4 | DATA: 5 | FILE = MPLUS_Chapter2.csv; 6 | FORMAT = FREE; 7 | 8 | DEFINE: 9 | age85 = age - 85; 10 | 11 | VARIABLE: 12 | NAMES = PersonID cog age grip sexMW demgroup; 13 | USEVARIABLES = cog age85; 14 | MISSING = ALL (-9999); 15 | 16 | ANALYSIS: 17 | ESTIMATOR = ML; 18 | PROCESSORS = 4; 19 | 20 | MODEL: 21 | cog ON age85; 22 | -------------------------------------------------------------------------------- /Chapters/02/MPLUS_Chapter2/MPLUS_Chapter2_cEq4_AddOriginalAge.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 2.4: Adding Original Age Instead 3 | 4 | DATA: 5 | FILE = MPLUS_Chapter2.csv; 6 | FORMAT = FREE; 7 | 8 | VARIABLE: 9 | NAMES = PersonID cog age grip sexMW demgroup; 10 | USEVARIABLES = cog age; 11 | MISSING = ALL (-9999); 12 | 13 | ANALYSIS: 14 | ESTIMATOR = ML; 15 | PROCESSORS = 4; 16 | 17 | MODEL: 18 | cog ON age; 19 | -------------------------------------------------------------------------------- /Chapters/02/MPLUS_Chapter2/MPLUS_Chapter2_dEq6_AddGrip9.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 2.6: Adding Grip (0=9) 3 | 4 | DATA: 5 | FILE = MPLUS_Chapter2.csv; 6 | FORMAT = FREE; 7 | 8 | DEFINE: 9 | age85 = age - 85; 10 | grip9 = grip - 9; 11 | 12 | VARIABLE: 13 | NAMES = PersonID cog age grip sexMW demgroup; 14 | USEVARIABLES = cog age85 grip9; 15 | MISSING = ALL (-9999); 16 | 17 | ANALYSIS: 18 | ESTIMATOR = ML; 19 | PROCESSORS = 4; 20 | 21 | MODEL: 22 | cog ON age85 grip9 (bage85 bgrip9); 23 | 24 | MODEL TEST: 25 | ! Model R2 Test 26 | bage85=0; 27 | bgrip9=0; 28 | -------------------------------------------------------------------------------- /Chapters/02/MPLUS_Chapter2/MPLUS_Chapter2_eEq7_AddSexMW.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 2.7: Adding Sex (0=M, 1=W) 3 | 4 | DATA: 5 | FILE = MPLUS_Chapter2.csv; 6 | FORMAT = FREE; 7 | 8 | DEFINE: 9 | age85 = age - 85; 10 | grip9 = grip - 9; 11 | 12 | VARIABLE: 13 | NAMES = PersonID cog age grip sexMW demgroup; 14 | USEVARIABLES = cog sexMW age85 grip9; 15 | MISSING = ALL (-9999); 16 | 17 | ANALYSIS: 18 | ESTIMATOR = ML; 19 | PROCESSORS = 4; 20 | 21 | MODEL: 22 | cog ON age85 grip9 sexMW (bage85 bgrip9 bsexMW); 23 | 24 | MODEL TEST: 25 | ! Model R2 Test 26 | bage85=0; 27 | bgrip9=0; 28 | bsexMW=0; 29 | -------------------------------------------------------------------------------- /Chapters/02/MPLUS_Chapter2/MPLUS_Chapter2_fEq6_AddSexWM.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 2.7: Adding Sex (1=M 0=W) 3 | 4 | DATA: 5 | FILE = MPLUS_Chapter2.csv; 6 | FORMAT = FREE; 7 | 8 | DEFINE: 9 | age85 = age - 85; 10 | grip9 = grip - 9; 11 | IF sexMW EQ 0 THEN sexWM=1; 12 | IF sexMW EQ 1 THEN sexWM=0; 13 | 14 | VARIABLE: 15 | NAMES = PersonID cog age grip sexMW demgroup; 16 | USEVARIABLES = cog age85 grip9 sexWM; 17 | MISSING = ALL (-9999); 18 | 19 | ANALYSIS: 20 | ESTIMATOR = ML; 21 | PROCESSORS = 4; 22 | 23 | MODEL: 24 | cog ON age85 grip9 sexWM; 25 | -------------------------------------------------------------------------------- /Chapters/02/MPLUS_Chapter2/MPLUS_Chapter2_gEq8_AddDemNFDemNC.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 2.8: Adding Dementia Group 3 | Using Manual Group Contrasts so Reference=None 4 | 5 | DATA: 6 | FILE = MPLUS_Chapter2.csv; 7 | FORMAT = FREE; 8 | 9 | DEFINE: 10 | age85 = age - 85; 11 | grip9 = grip - 9; 12 | IF demgroup EQ 1 THEN demNF=0; 13 | IF demgroup EQ 1 THEN demNC=0; 14 | IF demgroup EQ 2 THEN demNF=1; 15 | IF demgroup EQ 2 THEN demNC=0; 16 | IF demgroup EQ 3 THEN demNF=0; 17 | IF demgroup EQ 3 THEN demNC=1; 18 | 19 | VARIABLE: 20 | NAMES = PersonID cog age grip sexMW demgroup; 21 | USEVARIABLES = cog sexMW age85 grip9 demNF demNC; 22 | MISSING = ALL (-9999); 23 | 24 | ANALYSIS: 25 | ESTIMATOR = ML; 26 | PROCESSORS = 4; 27 | 28 | MODEL: 29 | cog ON age85 grip9 sexMW (bage85 bgrip9 bsexMW); 30 | cog ON demNF demNC (bdemNF bdemNC); 31 | 32 | MODEL TEST: 33 | ! Omnibus Dementia Group Test 34 | bdemNF=0; 35 | bdemNC=0; 36 | 37 | MODEL CONSTRAINT: 38 | NEW(est1); 39 | ! est1: Future vs Current 40 | est1 = -1*bdemNF + 1*bdemNC; 41 | -------------------------------------------------------------------------------- /Chapters/02/MPLUS_Chapter2/MPLUS_Chapter2_hEq9_AddAge85byGrip9.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 2.9: Adding Age by Grip Interaction 3 | Age (0=85), Grip (0=9) 4 | 5 | DATA: 6 | FILE = MPLUS_Chapter2.csv; 7 | FORMAT = FREE; 8 | 9 | DEFINE: 10 | age85 = age - 85; 11 | grip9 = grip - 9; 12 | IF demgroup EQ 1 THEN demNF=0; 13 | IF demgroup EQ 1 THEN demNC=0; 14 | IF demgroup EQ 2 THEN demNF=1; 15 | IF demgroup EQ 2 THEN demNC=0; 16 | IF demgroup EQ 3 THEN demNF=0; 17 | IF demgroup EQ 3 THEN demNC=1; 18 | agegrip = age85*grip9; 19 | 20 | VARIABLE: 21 | NAMES = PersonID cog age grip sexMW demgroup; 22 | USEVARIABLES = cog sexMW age85 grip9 demNF demNC agegrip; 23 | MISSING = ALL (-9999); 24 | 25 | ANALYSIS: 26 | ESTIMATOR = ML; 27 | PROCESSORS = 4; 28 | 29 | OUTPUT: 30 | TECH3; 31 | 32 | MODEL: 33 | cog ON age85 grip9 sexMW (bage85 bgrip9 bsexMW); 34 | cog ON demNF demNC (bdemNF bdemNC); 35 | cog ON agegrip (bagegrip); 36 | [cog] (int); 37 | 38 | MODEL TEST: 39 | ! Model R2 Test 40 | bage85=0; 41 | bgrip9=0; 42 | bsexMW=0; 43 | bdemNF=0; 44 | bdemNC=0; 45 | bagegrip=0; 46 | 47 | MODEL CONSTRAINT: 48 | NEW(est1-est16); 49 | ! est1: Future vs Current 50 | est1 = -1*bdemNF + 1*bdemNC; 51 | ! est2: Age Slope at Grip Strength = 6 52 | est2 = bage85*1 - bagegrip*3; 53 | ! est3: Age Slope at Grip Strength = 9 54 | est3 = bage85*1 + bagegrip*0; 55 | ! est4: Age Slope at Grip Strength = 12 56 | est4 = bage85*1 + bagegrip*3; 57 | ! est5: Grip Strength Slope at Age = 80 58 | est5 = bgrip9*1 - bagegrip*5; 59 | ! est6: Grip Strength Slope at Age = 85 60 | est6 = bgrip9*1 + bagegrip*0; 61 | ! est7: Grip Strength Slope at Age = 90 62 | est7 = bgrip9*1 + bagegrip*5; 63 | ! est8: Cognition at Grip = 12 Age = 80 64 | est8 = int*1 - bage85*5 + bgrip9*3 - bagegrip*15; 65 | ! est9: Cognition at Grip = 12 Age = 85 66 | est9 = int*1 + bage85*0 + bgrip9*3 + bagegrip*0; 67 | ! est10: Cognition at Grip = 12 Age = 90 68 | est10 = int*1 + bage85*5 + bgrip9*3 + bagegrip*15; 69 | ! est11: Cognition at Grip = 9 Age = 80 70 | est11 = int*1 - bage85*5 + bgrip9*0 + bagegrip*0; 71 | ! est12: Cognition at Grip = 9 Age = 85 72 | est12 = int*1 + bage85*0 + bgrip9*0 + bagegrip*0; 73 | ! est13: Cognition at Grip = 9 Age = 90 74 | est13 = int*1 + bage85*5 + bgrip9*0 + bagegrip*0; 75 | ! est14: Cognition at Grip = 6 Age = 80 76 | est14 = int*1 - bage85*5 - bgrip9*3 + bagegrip*15; 77 | ! est15: Cognition at Grip = 6 Age = 85 78 | est15 = int*1 + bage85*0 - bgrip9*3 + bagegrip*0; 79 | ! est16: Cognition at Grip = 6 Age = 90 80 | est16 = int*1 + bage85*5 - bgrip9*3 - bagegrip*15; 81 | -------------------------------------------------------------------------------- /Chapters/02/MPLUS_Chapter2/MPLUS_Chapter2_iEq9_AddAge80byGrip12.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 2.9: Adding Age by Grip Interaction 3 | Age (0=80), Grip (0=12) 4 | 5 | DATA: 6 | FILE = MPLUS_Chapter2.csv; 7 | FORMAT = FREE; 8 | 9 | DEFINE: 10 | age80 = age - 80; 11 | grip12 = grip - 12; 12 | IF demgroup EQ 1 THEN demNF=0; 13 | IF demgroup EQ 1 THEN demNC=0; 14 | IF demgroup EQ 2 THEN demNF=1; 15 | IF demgroup EQ 2 THEN demNC=0; 16 | IF demgroup EQ 3 THEN demNF=0; 17 | IF demgroup EQ 3 THEN demNC=1; 18 | agegrip = age80*grip12; 19 | 20 | VARIABLE: 21 | NAMES = PersonID cog age grip sexMW demgroup; 22 | USEVARIABLES = cog sexMW age80 grip12 demNF demNC agegrip; 23 | MISSING = ALL (-9999); 24 | 25 | ANALYSIS: 26 | ESTIMATOR = ML; 27 | PROCESSORS = 4; 28 | 29 | MODEL: 30 | cog ON age80 grip12 sexMW (bage80 bgrip12 bsexMW); 31 | cog ON demNF demNC (bdemNF bdemNC); 32 | cog ON agegrip (bagegrip); 33 | 34 | MODEL CONSTRAINT: 35 | NEW(est1); 36 | ! est1: Future vs Current 37 | est1 = -1*bdemNF + 1*bdemNC; 38 | -------------------------------------------------------------------------------- /Chapters/02/MPLUS_Chapter2/MPLUS_Chapter2_jEq9_AddAge90byGrip6.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 2.9: Adding Age by Grip Interaction 3 | Age (0=90), Grip (0=6) 4 | 5 | DATA: 6 | FILE = MPLUS_Chapter2.csv; 7 | FORMAT = FREE; 8 | 9 | DEFINE: 10 | age90 = age - 90; 11 | grip6 = grip - 6; 12 | IF demgroup EQ 1 THEN demNF=0; 13 | IF demgroup EQ 1 THEN demNC=0; 14 | IF demgroup EQ 2 THEN demNF=1; 15 | IF demgroup EQ 2 THEN demNC=0; 16 | IF demgroup EQ 3 THEN demNF=0; 17 | IF demgroup EQ 3 THEN demNC=1; 18 | agegrip = age90*grip6; 19 | 20 | VARIABLE: 21 | NAMES = PersonID cog age grip sexMW demgroup; 22 | USEVARIABLES = cog sexMW age90 grip6 demNF demNC agegrip; 23 | MISSING = ALL (-9999); 24 | 25 | ANALYSIS: 26 | ESTIMATOR = ML; 27 | PROCESSORS = 4; 28 | 29 | MODEL: 30 | cog ON age90 grip6 sexMW (bage90 bgrip6 bsexMW); 31 | cog ON demNF demNC (bdemNF bdemNC); 32 | cog ON agegrip (bagegrip); 33 | 34 | MODEL CONSTRAINT: 35 | NEW(est1); 36 | ! est1: Future vs Current 37 | est1 = -1*bdemNF + 1*bdemNC; 38 | -------------------------------------------------------------------------------- /Chapters/02/MPLUS_Chapter2/MPLUS_Chapter2_kEq13_AddSexMWbyDemNFNC.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 2.13: Adding Sex by Dementia Interaction 3 | Sex (0=Men), Dementia (0=None) 4 | 5 | DATA: 6 | FILE = MPLUS_Chapter2.csv; 7 | FORMAT = FREE; 8 | 9 | DEFINE: 10 | age85 = age - 85; 11 | grip9 = grip - 9; 12 | IF demgroup EQ 1 THEN demNF=0; 13 | IF demgroup EQ 1 THEN demNC=0; 14 | IF demgroup EQ 2 THEN demNF=1; 15 | IF demgroup EQ 2 THEN demNC=0; 16 | IF demgroup EQ 3 THEN demNF=0; 17 | IF demgroup EQ 3 THEN demNC=1; 18 | agegrip = age85*grip9; 19 | sexNF = sexMW*demNF; 20 | sexNC = sexMW*demNC; 21 | 22 | VARIABLE: 23 | NAMES = PersonID cog age grip sexMW demgroup; 24 | USEVARIABLES = cog sexMW age85 grip9 demNF demNC agegrip sexNF sexNC; 25 | MISSING = ALL (-9999); 26 | 27 | ANALYSIS: 28 | ESTIMATOR = ML; 29 | PROCESSORS = 4; 30 | 31 | OUTPUT: 32 | TECH3; 33 | 34 | MODEL: 35 | cog ON age85 grip9 sexMW (bage85 bgrip9 bsexMW); 36 | cog ON demNF demNC (bdemNF bdemNC); 37 | cog ON agegrip sexNF sexNC (bagegrip bsexNF bsexNC); 38 | [cog] (int); 39 | 40 | MODEL TEST: 41 | ! Omnibus Dementia*Sex Interaction Test 42 | bsexNF=0; 43 | bsexNC=0; 44 | 45 | MODEL CONSTRAINT: 46 | NEW(est1-est18); 47 | ! est1: Cognition for Men None 48 | est1 = int*1 + bsexMW*0 + bdemNF*0 + bdemNC*0 + bsexNF*0 + bsexNC*0; 49 | ! est2: Cognition for Women None 50 | est2 = int*1 + bsexMW*1 + bdemNF*0 + bdemNC*0 + bsexNF*0 + bsexNC*0; 51 | ! est3: Cognition for Men Future 52 | est3 = int*1 + bsexMW*0 + bdemNF*1 + bdemNC*0 + bsexNF*0 + bsexNC*0; 53 | ! est4: Cognition for Women Future 54 | est4 = int*1 + bsexMW*1 + bdemNF*1 + bdemNC*0 + bsexNF*1 + bsexNC*0; 55 | ! est5: Cognition for Men Current 56 | est5 = int*1 + bsexMW*0 + bdemNF*0 + bdemNC*1 + bsexNF*0 + bsexNC*0; 57 | ! est6: Cognition for Women Current 58 | est6 = int*1 + bsexMW*1 + bdemNF*0 + bdemNC*1 + bsexNF*0 + bsexNC*1; 59 | ! est7: Sex Difference for No Dementia 60 | est7 = bsexMW*1 + bsexNF*0 + bsexNC*0; 61 | ! est8: Sex Difference for Future Dementia 62 | est8 = bsexMW*1 + bsexNF*1 + bsexNC*0; 63 | ! est9: Sex Difference for Current Dementia 64 | est9 = bsexMW*1 + bsexNF*0 + bsexNC*1; 65 | ! est10: None-Future Difference for Men 66 | est10 = bdemNF*1 + bsexNF*0; 67 | ! est11: None-Future Difference for Women 68 | est11 = bdemNF*1 + bsexNF*1; 69 | ! est12: None-Current Difference for Men 70 | est12 = bdemNC*1 + bsexNC*0; 71 | ! est13: None-Current Difference for Women 72 | est13 = bdemNC*1 + bsexNC*1; 73 | ! est14: Future-Current Difference for Men 74 | est14 = -1*bdemNF + 1*bdemNC + 0*bsexNF + 0*bsexNC; 75 | ! est15: Future-Current Difference for Women 76 | est15 = -1*bdemNF + 1*bdemNC - 1*bsexNF + 1*bsexNC; 77 | ! est16: None-Future Sex Difference 78 | est16 = 1*bsexNF; 79 | ! est17: None-Current Sex Difference 80 | est17 = 1*bsexNC; 81 | ! est18: Future-Current Sex Difference 82 | est18 = -1*bsexNF + 1*bsexNC; 83 | -------------------------------------------------------------------------------- /Chapters/02/MPLUS_Chapter2/MPLUS_Chapter2_lEq13_AddSexWMbyDemNFNC.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 2.13: Adding Sex by Dementia Interaction 3 | Sex (0=Women), Dementia (0=None) 4 | 5 | DATA: 6 | FILE = MPLUS_Chapter2.csv; 7 | FORMAT = FREE; 8 | 9 | DEFINE: 10 | age85 = age - 85; 11 | grip9 = grip - 9; 12 | IF sexMW EQ 0 THEN sexWM=1; 13 | IF sexMW EQ 1 THEN sexWM=0; 14 | IF demgroup EQ 1 THEN demNF=0; 15 | IF demgroup EQ 1 THEN demNC=0; 16 | IF demgroup EQ 2 THEN demNF=1; 17 | IF demgroup EQ 2 THEN demNC=0; 18 | IF demgroup EQ 3 THEN demNF=0; 19 | IF demgroup EQ 3 THEN demNC=1; 20 | agegrip = age85*grip9; 21 | sexNF = sexWM*demNF; 22 | sexNC = sexWM*demNC; 23 | 24 | VARIABLE: 25 | NAMES = PersonID cog age grip sexMW demgroup; 26 | USEVARIABLES = cog age85 grip9 sexWM demNF demNC agegrip sexNF sexNC; 27 | MISSING = ALL (-9999); 28 | 29 | ANALYSIS: 30 | ESTIMATOR = ML; 31 | PROCESSORS = 4; 32 | 33 | MODEL: 34 | cog ON age85 grip9 sexWM (bage85 bgrip9 bsexWM); 35 | cog ON demNF demNC (bdemNF bdemNC); 36 | cog ON agegrip sexNF sexNC (bagegrip bsexNF bsexNC); 37 | -------------------------------------------------------------------------------- /Chapters/02/MPLUS_Chapter2/MPLUS_Chapter2_mEq15_AddSexMWbyDemFNFC.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 2.15: Adding Sex by Dementia Interaction 3 | Sex (0=Men), Dementia (0=Future) 4 | 5 | DATA: 6 | FILE = MPLUS_Chapter2.csv; 7 | FORMAT = FREE; 8 | 9 | DEFINE: 10 | age85 = age - 85; 11 | grip9 = grip - 9; 12 | IF demgroup EQ 1 THEN demFN=1; 13 | IF demgroup EQ 1 THEN demFC=0; 14 | IF demgroup EQ 2 THEN demFN=0; 15 | IF demgroup EQ 2 THEN demFC=0; 16 | IF demgroup EQ 3 THEN demFN=0; 17 | IF demgroup EQ 3 THEN demFC=1; 18 | agegrip = age85*grip9; 19 | sexFN = sexMW*demFN; 20 | sexFC = sexMW*demFC; 21 | 22 | VARIABLE: 23 | NAMES = PersonID cog age grip sexMW demgroup; 24 | USEVARIABLES = cog sexMW age85 grip9 demFN demFC agegrip sexFN sexFC; 25 | MISSING = ALL (-9999); 26 | 27 | ANALYSIS: 28 | ESTIMATOR = ML; 29 | PROCESSORS = 4; 30 | 31 | MODEL: 32 | cog ON age85 grip9 sexMW (bage85 bgrip9 bsexMW); 33 | cog ON demFN demFC (bdemFN bdemFC); 34 | cog ON agegrip sexFN sexFC (bagegrip bsexFN bsexFC); 35 | -------------------------------------------------------------------------------- /Chapters/02/MPLUS_Chapter2/MPLUS_Chapter2_nEq15_AddSexWMbyDemFNFC.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 2.15: Adding Sex by Dementia Interaction 3 | Sex (0=Women), Dementia (0=Future) 4 | 5 | DATA: 6 | FILE = MPLUS_Chapter2.csv; 7 | FORMAT = FREE; 8 | 9 | DEFINE: 10 | age85 = age - 85; 11 | grip9 = grip - 9; 12 | IF sexMW EQ 0 THEN sexWM=1; 13 | IF sexMW EQ 1 THEN sexWM=0; 14 | IF demgroup EQ 1 THEN demFN=1; 15 | IF demgroup EQ 1 THEN demFC=0; 16 | IF demgroup EQ 2 THEN demFN=0; 17 | IF demgroup EQ 2 THEN demFC=0; 18 | IF demgroup EQ 3 THEN demFN=0; 19 | IF demgroup EQ 3 THEN demFC=1; 20 | agegrip = age85*grip9; 21 | sexFN = sexWM*demFN; 22 | sexFC = sexWM*demFC; 23 | 24 | VARIABLE: 25 | NAMES = PersonID cog age grip sexMW demgroup; 26 | USEVARIABLES = cog age85 grip9 sexWM demFN demFC agegrip sexFN sexFC; 27 | MISSING = ALL (-9999); 28 | 29 | ANALYSIS: 30 | ESTIMATOR = ML; 31 | PROCESSORS = 4; 32 | 33 | MODEL: 34 | cog ON age85 grip9 sexWM (bage85 bgrip9 bsexWM); 35 | cog ON demFN demFC (bdemFN bdemFC); 36 | cog ON agegrip sexFN sexFC (bagegrip bsexFN bsexFC); 37 | -------------------------------------------------------------------------------- /Chapters/02/MPLUS_Chapter2/MPLUS_Chapter2_oEq16_AddSexMWbyDemCNCF.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 2.16: Adding Sex by Dementia Interaction 3 | Sex (0=Men), Dementia (0=Current) 4 | 5 | DATA: 6 | FILE = MPLUS_Chapter2.csv; 7 | FORMAT = FREE; 8 | 9 | DEFINE: 10 | age85 = age - 85; 11 | grip9 = grip - 9; 12 | IF demgroup EQ 1 THEN demCN=1; 13 | IF demgroup EQ 1 THEN demCF=0; 14 | IF demgroup EQ 2 THEN demCN=0; 15 | IF demgroup EQ 2 THEN demCF=1; 16 | IF demgroup EQ 3 THEN demCN=0; 17 | IF demgroup EQ 3 THEN demCF=0; 18 | agegrip = age85*grip9; 19 | sexCN = sexMW*demCN; 20 | sexCF = sexMW*demCF; 21 | 22 | VARIABLE: 23 | NAMES = PersonID cog age grip sexMW demgroup; 24 | USEVARIABLES = cog sexMW age85 grip9 demCN demCF agegrip sexCN sexCF; 25 | MISSING = ALL (-9999); 26 | 27 | ANALYSIS: 28 | ESTIMATOR = ML; 29 | PROCESSORS = 4; 30 | 31 | MODEL: 32 | cog ON age85 grip9 sexMW (bage85 bgrip9 bsexMW); 33 | cog ON demCN demCF (bdemCN bdemCF); 34 | cog ON agegrip sexCN sexCF (bagegrip bsexCN bsexCF); 35 | -------------------------------------------------------------------------------- /Chapters/02/MPLUS_Chapter2/MPLUS_Chapter2_pEq16_AddSexWMbyDemCNCF.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 2.16: Adding Sex by Dementia Interaction 3 | Sex (0=Women), Dementia (0=Current) 4 | 5 | DATA: 6 | FILE = MPLUS_Chapter2.csv; 7 | FORMAT = FREE; 8 | 9 | DEFINE: 10 | age85 = age - 85; 11 | grip9 = grip - 9; 12 | IF sexMW EQ 0 THEN sexWM=1; 13 | IF sexMW EQ 1 THEN sexWM=0; 14 | IF demgroup EQ 1 THEN demCN=1; 15 | IF demgroup EQ 1 THEN demCF=0; 16 | IF demgroup EQ 2 THEN demCN=0; 17 | IF demgroup EQ 2 THEN demCF=1; 18 | IF demgroup EQ 3 THEN demCN=0; 19 | IF demgroup EQ 3 THEN demCF=0; 20 | agegrip = age85*grip9; 21 | sexCN = sexWM*demCN; 22 | sexCF = sexWM*demCF; 23 | 24 | VARIABLE: 25 | NAMES = PersonID cog age grip sexMW demgroup; 26 | USEVARIABLES = cog age85 grip9 sexWM demCN demCF agegrip sexCN sexCF; 27 | MISSING = ALL (-9999); 28 | 29 | ANALYSIS: 30 | ESTIMATOR = ML; 31 | PROCESSORS = 4; 32 | 33 | MODEL: 34 | cog ON age85 grip9 sexWM (bage85 bgrip9 bsexWM); 35 | cog ON demCN demCF (bdemCN bdemCF); 36 | cog ON agegrip sexCN sexCF (bagegrip bsexCN bsexCF); 37 | -------------------------------------------------------------------------------- /Chapters/02/MPLUS_Chapter2/MPLUS_Chapter2_qEq17_AddAgeSexGripSex.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 2.17: Adding Age by Sex and Grip by Sex Interactions 3 | Age (0=85), Grip (0=9), Sex (0=Men), Dementia (0=None) 4 | 5 | DATA: 6 | FILE = MPLUS_Chapter2.csv; 7 | FORMAT = FREE; 8 | 9 | DEFINE: 10 | age85 = age - 85; 11 | grip9 = grip - 9; 12 | IF demgroup EQ 1 THEN demNF=0; 13 | IF demgroup EQ 1 THEN demNC=0; 14 | IF demgroup EQ 2 THEN demNF=1; 15 | IF demgroup EQ 2 THEN demNC=0; 16 | IF demgroup EQ 3 THEN demNF=0; 17 | IF demgroup EQ 3 THEN demNC=1; 18 | agegrip = age85*grip9; 19 | sexNF = sexMW*demNF; 20 | sexNC = sexMW*demNC; 21 | agesex = age85*sexMW; 22 | gripsex = grip9*sexMW; 23 | 24 | VARIABLE: 25 | NAMES = PersonID cog age grip sexMW demgroup; 26 | USEVARIABLES = cog sexMW age85 grip9 demNF demNC agegrip sexNF sexNC agesex gripsex; 27 | MISSING = ALL (-9999); 28 | 29 | ANALYSIS: 30 | ESTIMATOR = ML; 31 | PROCESSORS = 4; 32 | 33 | MODEL: 34 | cog ON age85 grip9 sexMW (bage85 bgrip9 bsexMW); 35 | cog ON demNF demNC (bdemNF bdemNC); 36 | cog ON agegrip sexNF sexNC (bagegrip bsexNF bsexNC); 37 | cog ON agesex gripsex (bagesex bgripsex); 38 | 39 | MODEL CONSTRAINT: 40 | NEW(est1-est16); 41 | ! est1: Age for Men 42 | est1 = bage85*1 + bagesex*0; 43 | ! est2: Age for Women 44 | est2 = bage85*1 + bagesex*1; 45 | ! est3: Grip for Men 46 | est3 = bgrip9*1 + bgripsex*0; 47 | ! est4: Grip for Women 48 | est4 = bgrip9*1 + bgripsex*1; 49 | ! est5: Sex for None 50 | est5 = bsexMW*1 + bsexNF*0 + bsexNC*0; 51 | ! est6: Sex for Future 52 | est6 = bsexMW*1 + bsexNF*1 + bsexNC*0; 53 | ! est7: Sex for Current 54 | est7 = bsexMW*1 + bsexNF*0 + bsexNC*1; 55 | ! est8: Men: None vs Future 56 | est8 = 1*bdemNF + 0*bdemNC + 0*bsexNF + 0*bsexNC; 57 | ! est9: Men: None vs Current 58 | est9 = 0*bdemNF + 1*bdemNC + 0*bsexNF + 0*bsexNC; 59 | ! est10: Men: Future vs Current 60 | est10 = -1*bdemNF + 1*bdemNC + 0*bsexNF + 0*bsexNC; 61 | ! est11: Women: None vs Future 62 | est11 = 1*bdemNF + 0*bdemNC + 1*bsexNF + 0*bsexNC; 63 | ! est12: Women: None vs Current 64 | est12 = 0*bdemNF + 1*bdemNC + 0*bsexNF + 1*bsexNC; 65 | ! est13: Women: Future vs Current 66 | est13 = -1*bdemNF + 1*bdemNC - 1*bsexNF + 1*bsexNC; 67 | ! est14: Sex by None vs Future 68 | est14 = 1*bsexNF + 0*bsexNC; 69 | ! est15: Sex by None vs Current 70 | est15 = 0*bsexNF + 1*bsexNC; 71 | ! est16: Sex by Future vs Current 72 | est16 = -1*bsexNF + 1*bsexNC; 73 | -------------------------------------------------------------------------------- /Chapters/02/MPLUS_Chapter2/MPLUS_Chapter2_rEq18_AddAgeGripSex.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 2.18: Adding Adding Age by Grip by Sex Three-Way Interaction 3 | Age (0=85), Grip (0=9), Sex (0=Men), Dementia (0=None) 4 | 5 | DATA: 6 | FILE = MPLUS_Chapter2.csv; 7 | FORMAT = FREE; 8 | 9 | DEFINE: 10 | age85 = age - 85; 11 | grip9 = grip - 9; 12 | IF demgroup EQ 1 THEN demNF=0; 13 | IF demgroup EQ 1 THEN demNC=0; 14 | IF demgroup EQ 2 THEN demNF=1; 15 | IF demgroup EQ 2 THEN demNC=0; 16 | IF demgroup EQ 3 THEN demNF=0; 17 | IF demgroup EQ 3 THEN demNC=1; 18 | agegrip = age85*grip9; 19 | sexNF = sexMW*demNF; 20 | sexNC = sexMW*demNC; 21 | agesex = age85*sexMW; 22 | gripsex = grip9*sexMW; 23 | ags = age85*grip9*sexMW; 24 | 25 | VARIABLE: 26 | NAMES = PersonID cog age grip sexMW demgroup; 27 | USEVARIABLES = cog sexMW age85 grip9 demNF demNC agegrip sexNF sexNC agesex gripsex ags; 28 | MISSING = ALL (-9999); 29 | 30 | ANALYSIS: 31 | ESTIMATOR = ML; 32 | PROCESSORS = 4; 33 | 34 | MODEL: 35 | cog ON age85 grip9 sexMW (bage85 bgrip9 bsexMW); 36 | cog ON demNF demNC (bdemNF bdemNC); 37 | cog ON agegrip sexNF sexNC (bagegrip bsexNF bsexNC); 38 | cog ON agesex gripsex ags (bagesex bgripsex bags); 39 | 40 | MODEL CONSTRAINT: 41 | NEW(est1-est18); 42 | ! est1: Age for Men 43 | est1 = bage85*1 + bagesex*0; 44 | ! est2: Age for Women 45 | est2 = bage85*1 + bagesex*1; 46 | ! est3: Grip for Men 47 | est3 = bgrip9*1 + bgripsex*0; 48 | ! est4: Grip for Women 49 | est4 = bgrip9*1 + bgripsex*1; 50 | ! est5: Sex for None 51 | est5 = bsexMW*1 + bsexNF*0 + bsexNC*0; 52 | ! est6: Sex for Future 53 | est6 = bsexMW*1 + bsexNF*1 + bsexNC*0; 54 | ! est7: Sex for Current 55 | est7 = bsexMW*1 + bsexNF*0 + bsexNC*1; 56 | ! est8: Men: None vs Future 57 | est8 = 1*bdemNF + 0*bdemNC + 0*bsexNF + 0*bsexNC; 58 | ! est9: Men: None vs Current 59 | est9 = 0*bdemNF + 1*bdemNC + 0*bsexNF + 0*bsexNC; 60 | ! est10: Men: Future vs Current 61 | est10 = -1*bdemNF + 1*bdemNC + 0*bsexNF + 0*bsexNC; 62 | ! est11: Women: None vs Future 63 | est11 = 1*bdemNF + 0*bdemNC + 1*bsexNF + 0*bsexNC; 64 | ! est12: Women: None vs Current 65 | est12 = 0*bdemNF + 1*bdemNC + 0*bsexNF + 1*bsexNC; 66 | ! est13: Women: Future vs Current 67 | est13 = -1*bdemNF + 1*bdemNC - 1*bsexNF + 1*bsexNC; 68 | ! est14: Sex by None vs Future 69 | est14 = 1*bsexNF + 0*bsexNC; 70 | ! est15: Sex by None vs Current 71 | est15 = 0*bsexNF + 1*bsexNC; 72 | ! est16: Sex by Future vs Current 73 | est16 = -1*bsexNF + 1*bsexNC; 74 | ! est17: Age by Grip for Men 75 | est17 = 1*bagegrip + 0*bags; 76 | ! est18: Age by Grip for Women 77 | est18 = 1*bagegrip + 1*bags; 78 | -------------------------------------------------------------------------------- /Chapters/02/MPLUS_Chapter2/MPLUS_Chapter2_sEq13_Final.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 2.13: Final Reported Model 3 | Age (0=85), Grip (0=9), Sex (0=Men), Dementia (0=None) 4 | 5 | DATA: 6 | FILE = MPLUS_Chapter2.csv; 7 | FORMAT = FREE; 8 | 9 | DEFINE: 10 | age85 = age - 85; 11 | grip9 = grip - 9; 12 | IF demgroup EQ 1 THEN demNF=0; 13 | IF demgroup EQ 1 THEN demNC=0; 14 | IF demgroup EQ 2 THEN demNF=1; 15 | IF demgroup EQ 2 THEN demNC=0; 16 | IF demgroup EQ 3 THEN demNF=0; 17 | IF demgroup EQ 3 THEN demNC=1; 18 | agegrip = age85*grip9; 19 | sexNF = sexMW*demNF; 20 | sexNC = sexMW*demNC; 21 | 22 | VARIABLE: 23 | NAMES = PersonID cog age grip sexMW demgroup; 24 | USEVARIABLES = cog sexMW age85 grip9 demNF demNC agegrip sexNF sexNC; 25 | MISSING = ALL (-9999); 26 | 27 | ANALYSIS: 28 | ESTIMATOR = ML; 29 | PROCESSORS = 4; 30 | 31 | MODEL: 32 | cog ON age85 grip9 sexMW (bage85 bgrip9 bsexMW); 33 | cog ON demNF demNC (bdemNF bdemNC); 34 | cog ON agegrip sexNF sexNC (bagegrip bsexNF bsexNC); 35 | 36 | MODEL TEST: 37 | ! Omnibus Dementia*Sex Interaction Test 38 | bsexNF=0; 39 | bsexNC=0; 40 | 41 | MODEL CONSTRAINT: 42 | NEW(est1-est12); 43 | ! est1: Sex Difference for No Dementia 44 | est1 = bsexMW*1 + bsexNF*0 + bsexNC*0; 45 | ! est2: Sex Difference for Future Dementia 46 | est2 = bsexMW*1 + bsexNF*1 + bsexNC*0; 47 | ! est3: Sex Difference for Current Dementia 48 | est3 = bsexMW*1 + bsexNF*0 + bsexNC*1; 49 | ! est4: None-Future Difference for Men 50 | est4 = bdemNF*1 + bsexNF*0; 51 | ! est5: None-Future Difference for Women 52 | est5 = bdemNF*1 + bsexNF*1; 53 | ! est6: None-Current Difference for Men 54 | est6 = bdemNC*1 + bsexNC*0; 55 | ! est7: None-Current Difference for Women 56 | est7 = bdemNC*1 + bsexNC*1; 57 | ! est8: Future-Current Difference for Men 58 | est8 = -1*bdemNF + 1*bdemNC + 0*bsexNF + 0*bsexNC; 59 | ! est9: Future-Current Difference for Women 60 | est9 = -1*bdemNF + 1*bdemNC - 1*bsexNF + 1*bsexNC; 61 | ! est10: None-Future Sex Difference 62 | est10 = 1*bsexNF; 63 | ! est11: None-Current Sex Difference 64 | est11 = 1*bsexNC; 65 | ! est12: Future-Current Sex Difference 66 | est12 = -1*bsexNF + 1*bsexNC; 67 | -------------------------------------------------------------------------------- /Chapters/02/OCTO.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Chapters/02/OCTO.txt -------------------------------------------------------------------------------- /Chapters/02/R_Chapter2/dsL.R: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Chapters/02/R_Chapter2/dsL.R -------------------------------------------------------------------------------- /Chapters/02/R_Chapter2/hoffman-ch2.R: -------------------------------------------------------------------------------- 1 | # remove all elements for a clean start 2 | rm(list=ls(all=TRUE)) 3 | # Supplementary Material for Longitudinal Analysis: Modeling Within-Person Fluctuation and Change 4 | # Chapter 2: MPLUS Syntax and Output by Model 5 | 6 | ## @knitr LoadPackages 7 | require(sas7bdat) 8 | library(nlme) 9 | 10 | 11 | ## @knitr LoadData 12 | pathDir <- getwd() 13 | pathCh2 <- file.path(pathDir,"Chapters/02/SAS_Chapter2/SAS_Chapter2.sas7bdat") 14 | dsL2 <- read.sas7bdat(pathCh2, debug=TRUE) 15 | ds <- dsL2 16 | names(ds) 17 | str(ds) 18 | table(ds$sexMW, ds$demgroup) 19 | 20 | 21 | ## @knitr EmptyMeansModel 22 | m0 <- nlme::gls(cognition ~ 1, data=ds, method="ML") 23 | summary(m0) 24 | ds$m0 <- predict(m0) 25 | 26 | 27 | ## @knitr AddingAge(0=85) 28 | ds$age85 <- ds$age - 85 29 | # m1 <- nlme::gls(cognition ~ 1 + age85, data=ds, method="ML") 30 | m1 <- stats::glm(cognition ~ 1 + age85, data=ds) 31 | summary(m1) 32 | ds$m1 <- predict(m1) 33 | 34 | 35 | model <- m1 36 | logLik<- summary(model)$logLik 37 | deviance<- -2*logLik 38 | AIC<- AIC(model) 39 | BIC<- BIC(model) 40 | df.resid<- NA 41 | N<- summary(model)$dims$N 42 | p<- summary(model)$dims$p 43 | ids<- length(unique(ds$PersonID)) 44 | df.resid<- N-p 45 | mInfo<- data.frame("logLik" = logLik, 46 | "deviance"= deviance, 47 | "AIC" = AIC, "BIC" = BIC, 48 | "df.resid" = df.resid, "N" = N, 49 | "p" = p, "ids" = ids) 50 | t<- t(mInfo) 51 | rownames(t)<-colnames(mInfo) 52 | dsmInfo<- data.frame(new=t) 53 | colnames(dsmInfo) <- c("modelA") 54 | # dsmInfo$Coefficient <- rownames(dsmInfo) 55 | mA <- dsmInfo 56 | print(mA) 57 | -------------------------------------------------------------------------------- /Chapters/02/R_Chapter2/hoffman-ch2.Rmd: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Untitled" 3 | author: "Andrey Koval" 4 | date: "Monday, January 12, 2015" 5 | output: html_document 6 | --- 7 | 8 | 9 | ```{r, echo=F, message=F} 10 | library(knitr) 11 | opts_knit$set(root.dir='../../../') #Don't combine this call with any other chunk -especially one that uses file paths. 12 | ``` 13 | 14 | 15 | ```{r, echo=F, message=T} 16 | require(knitr) 17 | opts_chunk$set( 18 | results='show', 19 | message = TRUE, 20 | comment = NA, 21 | tidy = FALSE, 22 | # fig.height = 4.8, 23 | # fig.width = 6.5, 24 | out.width = NULL, 25 | fig.path = 'figure_rmd/', 26 | dev = "png", 27 | dpi = 70 28 | ) 29 | echoChunks <- FALSE 30 | warningChunks<- FALSE 31 | messageChunks<- FALSE 32 | outwidthChunks <- "90%" 33 | options(width=120) #So the output is 50% wider than the default. 34 | read_chunk("./Chapters/02/R_Chapter2/hoffman-ch2.R") # the file to which knitr calls for the chunks 35 | ``` 36 | 37 | 38 | ## Beginnings of modeling 39 | 40 | There are several packages in R suited to fit linear and non-linear models. Some of them that we will use are: 41 | - stats 42 | - nlme 43 | - lme4 44 | 45 | 46 | ### stats package 47 | 48 | - [Official Documentation](http://www.rdocumentation.org/packages/stats) 49 | - [lm()](http://www.rdocumentation.org/packages/stats/functions/lm) function 50 | - [glm()](http://www.rdocumentation.org/packages/stats/functions/glm) function 51 | 52 | 53 | ### nlme package 54 | - [Official Documentation](http://www.rdocumentation.org/packages/nlme) 55 | - [gls()](http://www.rdocumentation.org/packages/nlme/functions/gls) function 56 | - see a basic example of model result processing in the slides on [Statistical Modeling](http://ialsa.github.io/COAG-colloquium-2014F/2014-11-18-Statistical-Modeling.html#35) of the COAG [Colloquium series](http://ialsa.github.io/COAG-colloquium-2014F) on reproducible research. 57 | 58 | 59 | ### lme4 package 60 | - [Official Documentation](http://www.rdocumentation.org/packages/lme4) 61 | - [lmer](http://www.rdocumentation.org/packages/nlme/functions/gls) function 62 | - [lmer guide](http://htmlpreview.github.io/?https://github.com/andkov/Longitudinal_Models_of_Religiosity_NLSY97/blob/master/Vignettes/lmer/for%20Appendix/lmerGuide.html#adding-model-output) 63 | 64 | 65 | 66 | 67 | 68 | 69 | -------------------------------------------------------------------------------- /Chapters/02/SAS_Chapter2/SAS_Chapter2.sas7bdat: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Chapters/02/SAS_Chapter2/SAS_Chapter2.sas7bdat -------------------------------------------------------------------------------- /Chapters/02/hoffman-ch2.knit.md: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Untitled" 3 | author: "Andrey Koval" 4 | date: "Monday, January 12, 2015" 5 | output: html_document 6 | --- 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | -------------------------------------------------------------------------------- /Chapters/03/CHAP.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Chapters/03/CHAP.txt -------------------------------------------------------------------------------- /Chapters/03/Chapter3b_LRTs.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Chapters/03/Chapter3b_LRTs.xlsx -------------------------------------------------------------------------------- /Chapters/03/MPLUS_Chapter3a/MPLUS_Chapter3a.csv: -------------------------------------------------------------------------------- 1 | 1,1,55.957283963,57.806318788 2 | 2,1,53.751907541,58.943056442 3 | 3,1,53.255502297,59.149057693 4 | 4,1,44.796028615,44.561577796 5 | 5,1,47.155837804,50.087385986 6 | 6,1,45.030325245,46.902295792 7 | 7,1,45.531226704,50.682110797 8 | 8,1,53.204271854,59.202372304 9 | 9,1,44.922434442,54.122123839 10 | 10,1,49.547571598,57.493299841 11 | 11,1,48.216133309,53.842204966 12 | 12,1,43.26607867,52.729441781 13 | 13,1,53.421233182,61.840788524 14 | 14,1,51.872439533,56.283524602 15 | 15,1,59.348657824,67.106032056 16 | 16,1,59.550481021,62.876913731 17 | 17,1,44.476805682,55.212112947 18 | 18,1,44.752826003,53.59692632 19 | 19,1,49.205520003,53.472559197 20 | 20,1,37.533504082,47.00154487 21 | 21,1,49.779179708,55.929933738 22 | 22,1,45.176923516,51.270398055 23 | 23,1,46.278076819,50.948180215 24 | 24,1,58.407288685,63.25440177 25 | 25,1,42.482405437,48.164511936 26 | 26,2,46.155245033,52.525766026 27 | 27,2,46.639796291,55.424533465 28 | 28,2,62.130913441,63.61611513 29 | 29,2,52.106332761,59.279146508 30 | 30,2,47.570615071,56.986816807 31 | 31,2,40.532193155,47.430344319 32 | 32,2,53.939025905,60.229146044 33 | 33,2,47.215971313,54.697213928 34 | 34,2,45.34969795,57.026963303 35 | 35,2,53.054923017,61.110452154 36 | 36,2,46.883747598,56.313332471 37 | 37,2,55.695269628,62.728856626 38 | 38,2,51.433554916,49.669190235 39 | 39,2,49.505369424,58.536020666 40 | 40,2,55.959596477,68.616302796 41 | 41,2,48.446347249,57.425746359 42 | 42,2,50.49732145,60.902380259 43 | 43,2,52.045289549,59.969413052 44 | 44,2,52.572673115,56.576064094 45 | 45,2,51.946362571,61.393311514 46 | 46,2,52.925010805,66.092277209 47 | 47,2,58.082071372,65.533738256 48 | 48,2,49.309854627,55.304632273 49 | 49,2,51.55191299,62.173306839 50 | 50,2,47.419394763,56.029715171 51 | -------------------------------------------------------------------------------- /Chapters/03/MPLUS_Chapter3a/MPLUS_Chapter3a_aEq1_EmptyBPModel.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 3a.1: Empty Between-Person Model 3 | 4 | DATA: 5 | FILE = MPLUS_Chapter3a.csv; 6 | FORMAT = FREE; 7 | 8 | DATA WIDETOLONG: 9 | WIDE = outcome1-outcome2; 10 | LONG = outcome; 11 | IDVARIABLE = PersonID; 12 | REPETITION = time1; 13 | 14 | VARIABLE: 15 | NAMES = PersonID group outcome1 outcome2; 16 | USEVARIABLES = outcome; 17 | MISSING = ALL (-9999); 18 | CLUSTER = PersonID; 19 | 20 | ANALYSIS: 21 | ESTIMATOR = ML; 22 | PROCESSORS = 4; 23 | TYPE = TWOLEVEL RANDOM; 24 | 25 | MODEL: 26 | 27 | %WITHIN% 28 | outcome; 29 | 30 | %BETWEEN% 31 | [outcome]; 32 | outcome@0; 33 | -------------------------------------------------------------------------------- /Chapters/03/MPLUS_Chapter3a/MPLUS_Chapter3a_bEq2_EmptyWPModel.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 3a.2: Empty Within-Person Model 3 | 4 | DATA: 5 | FILE = MPLUS_Chapter3a.csv; 6 | FORMAT = FREE; 7 | 8 | DATA WIDETOLONG: 9 | WIDE = outcome1-outcome2; 10 | LONG = outcome; 11 | IDVARIABLE = PersonID; 12 | REPETITION = time1; 13 | 14 | VARIABLE: 15 | NAMES = PersonID group outcome1 outcome2; 16 | USEVARIABLES = outcome; 17 | MISSING = ALL (-9999); 18 | CLUSTER = PersonID; 19 | 20 | ANALYSIS: 21 | ESTIMATOR = ML; 22 | PROCESSORS = 4; 23 | TYPE = TWOLEVEL RANDOM; 24 | 25 | MODEL: 26 | 27 | %WITHIN% 28 | outcome; 29 | 30 | %BETWEEN% 31 | [outcome]; 32 | outcome; 33 | -------------------------------------------------------------------------------- /Chapters/03/MPLUS_Chapter3a/MPLUS_Chapter3a_cEq7_CondBPModel.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 3a.7: Conditional Between-Person Model (top of Eq. 3.7) 3 | Manual Contrasts for Time and Group 4 | 5 | DATA: 6 | FILE = MPLUS_Chapter3a.csv; 7 | FORMAT = FREE; 8 | 9 | DATA WIDETOLONG: 10 | WIDE = outcome1-outcome2; 11 | LONG = outcome; 12 | IDVARIABLE = PersonID; 13 | REPETITION = time1; 14 | 15 | DEFINE: 16 | treat = group - 1; 17 | 18 | VARIABLE: 19 | NAMES = PersonID group outcome1 outcome2; 20 | USEVARIABLES = outcome time1 treat; 21 | MISSING = ALL (-9999); 22 | CLUSTER = PersonID; 23 | WITHIN = time1; 24 | BETWEEN = treat; 25 | 26 | ANALYSIS: 27 | ESTIMATOR = ML; 28 | PROCESSORS = 4; 29 | TYPE = TWOLEVEL RANDOM; 30 | 31 | MODEL: 32 | 33 | %WITHIN% 34 | outcome (resvar); 35 | time | outcome ON time1; 36 | 37 | %BETWEEN% 38 | [outcome time] (int btime1); 39 | outcome@0 time@0; 40 | outcome time ON treat (btreat btimtreat); 41 | 42 | MODEL CONSTRAINT: 43 | NEW(est1-est8); 44 | ! est1: Mean: Control Group at Pre-Test 45 | est1 = int*1 + btime1*0 + btreat*0 + btimtreat*0; 46 | ! est2: Mean: Control Group at Post-Test 47 | est2 = int*1 + btime1*1 + btreat*0 + btimtreat*0; 48 | ! est3: Mean: Treatment Group at Pre-Test 49 | est3 = int*1 + btime1*0 + btreat*1 + btimtreat*0; 50 | ! est4: Mean: Treatment Group at Post-Test 51 | est4 = int*1 + btime1*1 + btreat*1 + btimtreat*1; 52 | ! est5: Time Effect for Control Group 53 | est5 = btime1*1 + btimtreat*0; 54 | ! est6: Time Effect for Treatment Group 55 | est6 = btime1*1 + btimtreat*1; 56 | ! est7: Group Effect at Pre-Tmplusest 57 | est7 = btreat*1 + btimtreat*0; 58 | ! est8: Group Effect at Post-Tmplusest 59 | est8 = btreat*1 + btimtreat*1; 60 | -------------------------------------------------------------------------------- /Chapters/03/MPLUS_Chapter3a/MPLUS_Chapter3a_dEq7_CondWPModel.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 3a.7: Conditional Within-Person Model (bottom of Eq. 3.7) 3 | Manual Contrasts for Time and Group 4 | 5 | DATA: 6 | FILE = MPLUS_Chapter3a.csv; 7 | FORMAT = FREE; 8 | 9 | DATA WIDETOLONG: 10 | WIDE = outcome1-outcome2; 11 | LONG = outcome; 12 | IDVARIABLE = PersonID; 13 | REPETITION = time1; 14 | 15 | DEFINE: 16 | treat = group - 1; 17 | 18 | VARIABLE: 19 | NAMES = PersonID group outcome1 outcome2; 20 | USEVARIABLES = outcome time1 treat; 21 | MISSING = ALL (-9999); 22 | CLUSTER = PersonID; 23 | WITHIN = time1; 24 | BETWEEN = treat; 25 | 26 | ANALYSIS: 27 | ESTIMATOR = ML; 28 | PROCESSORS = 4; 29 | TYPE = TWOLEVEL RANDOM; 30 | 31 | MODEL: 32 | 33 | %WITHIN% 34 | outcome (resvar); 35 | time | outcome ON time1; 36 | 37 | %BETWEEN% 38 | [outcome time] (int btime1); 39 | outcome time@0 (intvar); 40 | outcome time ON treat (btreat btimtreat); 41 | 42 | MODEL CONSTRAINT: 43 | NEW(est1-est9); 44 | ! est1: Mean: Control Group at Pre-Test 45 | est1 = int*1 + btime1*0 + btreat*0 + btimtreat*0; 46 | ! est2: Mean: Control Group at Post-Test 47 | est2 = int*1 + btime1*1 + btreat*0 + btimtreat*0; 48 | ! est3: Mean: Treatment Group at Pre-Test 49 | est3 = int*1 + btime1*0 + btreat*1 + btimtreat*0; 50 | ! est4: Mean: Treatment Group at Post-Test 51 | est4 = int*1 + btime1*1 + btreat*1 + btimtreat*1; 52 | ! est5: Time Effect for Control Group 53 | est5 = btime1*1 + btimtreat*0; 54 | ! est6: Time Effect for Treatment Group 55 | est6 = btime1*1 + btimtreat*1; 56 | ! est7: Group Effect at Pre-Tmplusest 57 | est7 = btreat*1 + btimtreat*0; 58 | ! est8: Group Effect at Post-Tmplusest 59 | est8 = btreat*1 + btimtreat*1; 60 | ! est9: Conditional Intraclass Correlation 61 | est9 = intvar/(intvar+resvar); 62 | -------------------------------------------------------------------------------- /Chapters/03/MPLUS_Chapter3b/MPLUS_Chapter3b_aEq10_BPANOVA.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 3b.10: Between-Person Independent ANOVA 3 | 4 | DATA: 5 | FILE = MPLUS_Chapter3b.csv; 6 | FORMAT = FREE; 7 | 8 | DATA LONGTOWIDE: 9 | LONG = rt; 10 | WIDE = rt1-rt6; 11 | IDVARIABLE = PersonID; 12 | REPETITION = session (1-6); 13 | 14 | DEFINE: 15 | ! Rescale original rt so Mplus will show all results 16 | rt = rt/10; 17 | 18 | VARIABLE: 19 | NAMES = PersonID session rt; 20 | USEVARIABLES = rt1-rt6; 21 | MISSING = ALL (-9999); 22 | 23 | ANALYSIS: 24 | ESTIMATOR = ML; 25 | PROCESSORS = 4; 26 | 27 | MODEL: 28 | rt1-rt6 (totvar); 29 | rt1-rt6 WITH rt1-rt6@0; 30 | [rt1-rt6] (mean1-mean6); 31 | 32 | MODEL TEST: 33 | ! Omnibus Test of Session Mean Differences 34 | 0=mean6-mean1; 35 | 0=mean6-mean2; 36 | 0=mean6-mean3; 37 | 0=mean6-mean4; 38 | 0=mean6-mean5; 39 | -------------------------------------------------------------------------------- /Chapters/03/MPLUS_Chapter3b/MPLUS_Chapter3b_bEq10_UnivRMANOVA.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 3b.10: Univariate Repeated Measures ANOVA 3 | 4 | DATA: 5 | FILE = MPLUS_Chapter3b.csv; 6 | FORMAT = FREE; 7 | 8 | DATA LONGTOWIDE: 9 | LONG = rt; 10 | WIDE = rt1-rt6; 11 | IDVARIABLE = PersonID; 12 | REPETITION = session (1-6); 13 | 14 | DEFINE: 15 | ! Rescale original rt so Mplus will show all results 16 | rt = rt/10; 17 | 18 | VARIABLE: 19 | NAMES = PersonID session rt; 20 | USEVARIABLES = rt1-rt6; 21 | MISSING = ALL (-9999); 22 | 23 | ANALYSIS: 24 | ESTIMATOR = ML; 25 | PROCESSORS = 4; 26 | 27 | OUTPUT: 28 | STDYX; 29 | 30 | MODEL: 31 | rt1-rt6 (totvar); 32 | rt1-rt6 WITH rt1-rt6 (totcov); 33 | [rt1-rt6] (mean1-mean6); 34 | 35 | MODEL TEST: 36 | ! Omnibus Test of Session Mean Differences 37 | 0=mean6-mean1; 38 | 0=mean6-mean2; 39 | 0=mean6-mean3; 40 | 0=mean6-mean4; 41 | 0=mean6-mean5; 42 | -------------------------------------------------------------------------------- /Chapters/03/MPLUS_Chapter3b/MPLUS_Chapter3b_cEq10_MultivRMANOVA.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Eq 3b.10: Multivariate Repeated Measures ANOVA 3 | 4 | DATA: 5 | FILE = MPLUS_Chapter3b.csv; 6 | FORMAT = FREE; 7 | 8 | DATA LONGTOWIDE: 9 | LONG = rt; 10 | WIDE = rt1-rt6; 11 | IDVARIABLE = PersonID; 12 | REPETITION = session (1-6); 13 | 14 | DEFINE: 15 | ! Rescale original rt so Mplus will show all results 16 | rt = rt/10; 17 | 18 | VARIABLE: 19 | NAMES = PersonID session rt; 20 | USEVARIABLES = rt1-rt6; 21 | MISSING = ALL (-9999); 22 | 23 | ANALYSIS: 24 | ESTIMATOR = ML; 25 | PROCESSORS = 4; 26 | 27 | OUTPUT: 28 | STDYX; 29 | 30 | MODEL: 31 | rt1-rt6; 32 | rt1-rt6 WITH rt1-rt6; 33 | [rt1-rt6] (mean1-mean6); 34 | 35 | MODEL TEST: 36 | ! Omnibus Test of Session Mean Differences 37 | 0=mean6-mean1; 38 | 0=mean6-mean2; 39 | 0=mean6-mean3; 40 | 0=mean6-mean4; 41 | 0=mean6-mean5; 42 | -------------------------------------------------------------------------------- /Chapters/03/R_Chapter3/figure_rmd/EmptyBP4.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Chapters/03/R_Chapter3/figure_rmd/EmptyBP4.png -------------------------------------------------------------------------------- /Chapters/03/R_Chapter3/figure_rmd/EmptyBP5.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Chapters/03/R_Chapter3/figure_rmd/EmptyBP5.png -------------------------------------------------------------------------------- /Chapters/03/R_Chapter3/figure_rmd/EmptyWP4.png: 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is of class... 16 | class(Y) 17 | 18 | # we can make it a matrix using matric() function 19 | Y <- matrix(Y,5,1,byrow=TRUE) # matrix (data,#rows,#columns,...) 20 | 21 | 22 | # create six data vectors of length 5 , one for each person (i) 23 | i1 <- c(1, 11, 11.5, 11.8, 10.3, 9.5) 24 | i2 <- c(2, 9, 9.8, 9.7, 9.6, 9.3) 25 | i3 <- c(3, 9, 7.8, 8.1, 9.1, 7.8) 26 | i4 <- c(4, 6.8, 7.9, 7, 7.8, 6.8) 27 | i5 <- c(5, 6.4, 6.2, 6.8, 7.1, 7.2) 28 | i6 <- c(6, 4, 5.6, 4.5, 5.2, 6.8) 29 | 30 | # combine 31 | data <- cbind(i1, i2, i3, i4, i5, i6) 32 | data 33 | 34 | class(data) 35 | X <- matrix(data,6,6, byrow=TRUE) 36 | X 37 | 38 | 39 | i <- paste0("i",1:6) 40 | vars <- c("id",paste0("t",1:5)) 41 | X 42 | rownames(X) <- i 43 | X 44 | colnames(X) <- vars 45 | X 46 | 47 | ds <- data.frame(X) 48 | ds 49 | 50 | p <- ggplot(ds, aes(x=1:6)) 51 | p <- geom_line(aes(y=t1)) 52 | 53 | 54 | 55 | 56 | dsLong <- reshape2::melt(ds, id.vars="id") 57 | dsLong <- dsLong[order(dsLong$id, dsLong$variable),] 58 | head(dsLong,12) 59 | dsLong$variable <- gsub(pattern="t", replacement='', x=dsLong$variable) 60 | head(dsLong,12) 61 | str(dsLong) 62 | dsLong$variable <- as.integer(dsLong$variable) 63 | str(dsLong) 64 | dsLong <- plyr::rename(dsLong,c("variable"="time", "value"="outcome")) 65 | ds <- dsLong 66 | head(ds) 67 | 68 | pathDir <- getwd() 69 | source(file.path(pathDir,"Scripts/Graphs/graphThemes.R")) 70 | p <- ggplot2::ggplot(ds,aes(x=time,y=outcome)) 71 | p <- p + geom_line(aes(group=id, color=factor(id))) 72 | p <- p + geom_point(aes(group=id, color=factor(id))) 73 | p <- p + theme1 74 | p <- p + scale_x_continuous(limits=c(1,5), breaks=seq(0,6)) 75 | p <- p + scale_y_continuous(limits=c(0,12), 76 | breaks=seq(0,13, by=2)) 77 | p <- p + labs(list( 78 | title="Hypothetical trajectories from slide 308", 79 | x="Occasion", y="Outcome")) 80 | p 81 | -------------------------------------------------------------------------------- /Chapters/03/SAS_Chapter3a/SAS_Chapter3a.sas7bdat: 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-------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Chapters/05/MPlus_Chapter5/Ch5_Mplus.pdf -------------------------------------------------------------------------------- /Chapters/05/MPlus_Chapter5/ELSA_MLMGROWTH_EMPTY.inp: -------------------------------------------------------------------------------- 1 | Title: ELSA MLM Hoffman Chapter 5 Extended Example 2 | 3 | Data: File is ELSA_LONG_n1000.dat ; 4 | 5 | Variable: Names are 6 | idauniq idahhw wgt year year2 wave wave2 age2 7 | dageyrs ddobyrs dyear0 dyrsobs dagefat dagemot 8 | dsex deduqual dethnic dhhsize dmarsta 9 | 10 | eclaind eclahh einchhg ejobfath edqualw1 eincind 11 | eclafath ewthphy ewthnfn ewthfin ewthinv ewthsav 12 | eincspn eincppn einchh eworksta 13 | 14 | balcupw0 balcamt0 bsmkqty bsmkevr bsmknow balcoft balcdlw 15 | 16 | hcvddia hrspdia hdigdia hmskdia hblddia hagdmoth 17 | hcodmoth hagdfath hcodfath hsrhscr hbminum hfvcltr 18 | hfevltr hlunglm hangdia hdibdia hcandia hpsydia 19 | hdgskgs hngskgs hmapprs hpulprs hdiaprs hsysprs 20 | hwlksec hcr5sec hiadsca hadlsca 21 | 22 | psspscr0 pc19sca pdepsca 23 | 24 | csrmscr cwrlnum caninum cprmscr cdwlnum; 25 | 26 | Missing are all (-9999); 27 | 28 | ! List of ALL variables used in model; 29 | USEVARIABLES ARE cdwlnum; ! Use in random int model; 30 | !USEVARIABLES ARE time cdwlnum; ! Use in linear time models; 31 | 32 | ! limit cases; 33 | ! USEOBSERVATIONS = ; 34 | 35 | ! Identify person-level nesting; 36 | CLUSTER = idauniq; 37 | ! Predictor variables measured within-persons (just time for now); 38 | WITHIN = ; ! Use in random int model; 39 | !WITHIN = time; ! Use in linear models; 40 | 41 | ! Predictor variables measured between-persons (none right now); 42 | BETWEEN = ; 43 | 44 | Define: age65=dageyrs-65; 45 | time=year; 46 | 47 | ANALYSIS: TYPE IS TWOLEVEL RANDOM; ! 2-level model with random slopes; 48 | ESTIMATOR IS ML; 49 | MODEL: 50 | !!!!! Model 1: Empty, Random Intercept Only Model; 51 | ! Level-1, time-level model; 52 | %WITHIN% ! Residual included by default; 53 | ; 54 | ! Level-2, person-level model; 55 | %BETWEEN% 56 | cdwlnum*; ! Random int included by default; 57 | 58 | !!!!! Model 2: Fixed Linear, Random Intercept Model; 59 | ! Level-1, time-level model; 60 | ! %WITHIN% ! Residual included by default; 61 | ! ? ! Fixed linear slope; 62 | ! Level-2, person-level model; 63 | ! %BETWEEN% 64 | ! cdwlnum* ! Random int included by default; 65 | ! ? ! No random linear variance; 66 | 67 | !!!!! Model 3: Random Linear Only Model; 68 | ! Level-1, time-level model; 69 | ! %WITHIN% ! Residual included by default; 70 | ! ? ! Fixed linear slope; 71 | ! Level-2, person-level model; 72 | ! %BETWEEN% 73 | ! cdwlnum* ! Random int included by default; 74 | ! ? ! Random linear variance; 75 | ! ? ! Int-Linear covariance; 76 | 77 | Output: sampstat; 78 | 79 | -------------------------------------------------------------------------------- /Chapters/05/R_Chapter5/.Rhistory: -------------------------------------------------------------------------------- 1 | # remove all elements for a clean start 2 | rm(list=ls(all=TRUE)) 3 | cat("\014") 4 | ## @knitr InstallPackage 5 | # source("./Scripts/Utility/InstallPackages.R") 6 | ## @knitr LoadPackages 7 | require(sas7bdat) # for inputting data 8 | library(dplyr) # for general data manipulation 9 | library(reshape2) # for data : wide <-> long 10 | library(psych) # data summary + etc 11 | library(ggplot2) # graphing 12 | library(nlme) # estimate mixed models | esp. gls() 13 | library(lme4) # estimate mixed models | esp. lmer() 14 | library(arm) # process model objects 15 | ## @knitr LoadData 16 | pathDir <- getwd() # get working directory, e.i. residence of .Rproj file 17 | pathFile <- file.path(pathDir,"Chapters/05/SAS_Chapter5/SAS_Chapter5.sas7bdat") # location of the file 18 | ds0 <- read.sas7bdat(pathFile, debug=TRUE) # import file 19 | # ds0 <- readRDS("~/GitHub/psy564/Data/Raw/ELSA/ds0_ELSA.rds") 20 | ds0 <- data.frame(ds0) # save as a data frame 21 | ## @knitr BasicDescriptive 22 | class(ds0) # what class? 23 | dim(ds0) # what dimensions? 24 | names(ds0) # what are column names? 25 | str(ds0) # what its structure? 26 | head(ds0) # what do first few lines look like? 27 | base::summary(ds0) # basic summary 28 | psych::describe(ds0) # summary by psych package 29 | table(ds0$wave)# one-way table 30 | ## @knitr StackData 31 | dsL <- ds0 32 | ## @knitr TweakLong 33 | dsM <- dsL 34 | ## @knitr dummyChunk 35 | #### Basic Graphs #### 36 | ## @knitr GraphingData0 37 | p <- ggplot2::ggplot(dsM,aes(x=wave,y=outcome)) # map data dimension 38 | p <- p + geom_line(aes(group=PersonID)) # draw lines and map unit of measurement 39 | p 40 | ## @knitr LoadGraphThemes 41 | baseSize <- 12 # set as the point of further reference 42 | theme1 <- ggplot2::theme_bw(base_size=baseSize) + 43 | ggplot2::theme(title=ggplot2::element_text(colour="gray20",size = baseSize+1)) + 44 | ggplot2::theme(axis.text=ggplot2::element_text(colour="gray40", size=baseSize-2)) + 45 | ggplot2::theme(axis.title=ggplot2::element_text(colour="gray40")) + 46 | ggplot2::theme(panel.border = ggplot2::element_rect(colour="gray80")) + 47 | ggplot2::theme(axis.ticks.length = grid::unit(0, "cm")) + 48 | ggplot2::theme(text = element_text(size =baseSize+7)) 49 | ## @knitr GraphingData1 50 | p <- ggplot2::ggplot(dsM,aes(x=wave,y=outcome)) 51 | p <- p + geom_line(aes(group=PersonID)) # draw lines 52 | p <- p + theme1 53 | p <- p + scale_x_continuous(limits=c(1,4), breaks=c(1:4)) # X axis 54 | p <- p + scale_y_continuous(limits=c(5,25), 55 | breaks=seq(5,25, by=5)) # Y axis 56 | p <- p + labs(list( 57 | title="Does outcome change over time?", # main title 58 | x="Wave of measurement", y="Performance on the outcome")) # axes titles 59 | p 60 | # remove all elements for a clean start 61 | rm(list=ls(all=TRUE)) 62 | cat("\014") 63 | ## @knitr InstallPackage 64 | # source("./Scripts/Utility/InstallPackages.R") 65 | ## @knitr LoadPackages 66 | require(sas7bdat) # for inputting data 67 | library(dplyr) # for general data manipulation 68 | library(reshape2) # for data : wide <-> long 69 | library(psych) # data summary + etc 70 | library(ggplot2) # graphing 71 | library(nlme) # estimate mixed models | esp. gls() 72 | library(lme4) # estimate mixed models | esp. lmer() 73 | library(arm) # process model objects 74 | ## @knitr LoadData 75 | pathDir <- getwd() # get working directory, e.i. residence of .Rproj file 76 | pathFile <- file.path(pathDir,"Chapters/05/SAS_Chapter5/SAS_Chapter5.sas7bdat") # location of the file 77 | ds0 <- read.sas7bdat(pathFile, debug=TRUE) # import file 78 | # ds0 <- readRDS("~/GitHub/psy564/Data/Raw/ELSA/ds0_ELSA.rds") 79 | ds0 <- data.frame(ds0) # save as a data frame 80 | ## @knitr BasicDescriptive 81 | class(ds0) # what class? 82 | dim(ds0) # what dimensions? 83 | names(ds0) # what are column names? 84 | str(ds0) # what its structure? 85 | head(ds0) # what do first few lines look like? 86 | base::summary(ds0) # basic summary 87 | psych::describe(ds0) # summary by psych package 88 | table(ds0$wave)# one-way table 89 | pathFile 90 | ds0 <- read.sas7bdat(pathFile, debug=TRUE) # import file 91 | -------------------------------------------------------------------------------- /Chapters/05/R_Chapter5/SimpleExample_Key.R: -------------------------------------------------------------------------------- 1 | # remove all elements for a clean start 2 | rm(list=ls(all=TRUE)) 3 | cat("\014") 4 | 5 | library(dplyr) 6 | library(lme4) 7 | library(ggplot2) 8 | 9 | #### Data entry #### 10 | y <- c(2,3,2,1,2,1,5,5) 11 | id <- c(1,1,1,1,2,2,2,2) 12 | ds <- data.frame(cbind(id,y)) 13 | ds 14 | ds$wave <- with(ds, ave( id, id, FUN = seq_along)) # sequential numbers 15 | ds 16 | 17 | ds1 <- ds[ds$id==1,] 18 | ds2 <- ds[ds$id==2,] 19 | 20 | lm(y ~ 1, ds1) 21 | lm(y ~ 1, ds2) 22 | 23 | 24 | 25 | # dplyr::group_by(ds,id) %>% dplyr::summarize(means = mean(y)) 26 | 27 | mean(ds[ds$id==1,"y"]) 28 | mean(ds[ds$id==2,"y"]) 29 | 30 | 31 | head(ds) 32 | 33 | #### Model m00 #### 34 | m00 <- lm(y ~ 1 ,ds) 35 | ds$m00 <- predict(m00) 36 | ds 37 | #### Model m01 #### 38 | m01 <- lm(y ~ 1 + wave, ds) 39 | ds$m01 <- predict(m01) 40 | ds 41 | #### Model m0* #### 42 | m0_1 <- lm(y ~ 1, ds1) 43 | m0_2 <- lm(y ~ 1, ds2) 44 | # # Automating grouping with dplyr 45 | # results<-ds %.% 46 | # group_by(id) %.% 47 | # do(model =lm(y ~ 1 , data = .)) 48 | # coef(results$model[[1]]) 49 | # coef(results$model[[2]]) 50 | ds1$m0_ <- predict(m0_1) 51 | ds2$m0_ <- predict(m0_2) 52 | dsa <- merge(ds, rbind(ds1,ds2)) 53 | ds 54 | 55 | 56 | #### Model m1* #### 57 | m1_1 <- lm(y ~ 1 + wave, ds1) 58 | m1_2 <- lm(y ~ 1 + wave, ds2) 59 | # # Automating grouping with dplyr 60 | # results<-ds %.% 61 | # group_by(id) %.% 62 | # do(model =lm(y ~ 1 + wave , data = .)) 63 | # coef(results$model[[1]]) 64 | # round(coef(results$model[[2]]),2) 65 | ds1$m1_ <- predict(m1_1) 66 | ds2$m1_ <- predict(m1_2) 67 | ds <- merge(ds, rbind(ds1,ds2)) 68 | ds 69 | 70 | #### Model m0 #### 71 | m0 <- lme4::lmer(y ~ 1 + (1|id) , data = ds) 72 | ranef(m0) 73 | fixef(m0) 74 | ds$m0 <- predict(m0) 75 | ds 76 | 77 | #### Model m0a #### 78 | m0a <- lme4::lmer(y ~ 1 + wave + (1|id) , data = ds) 79 | ranef(m0a) 80 | fixef(m0a) 81 | ds$m0a <- predict(m0a) 82 | ds 83 | 84 | #### Model m1 #### 85 | m1 <- lme4::lmer(y ~ 1 + wave + (1 + wave|id) , data = ds) 86 | ranef(m1) 87 | fixef(m1) 88 | ds$m1 <- predict(m1) 89 | ds 90 | 91 | 92 | #### Graphing #### 93 | 94 | 95 | baseSize <- 12 # set as the point of further reference 96 | theme1 <- ggplot2::theme_bw(base_size=baseSize) + 97 | ggplot2::theme(title=ggplot2::element_text(colour="gray20",size = baseSize+1)) + 98 | ggplot2::theme(axis.text=ggplot2::element_text(colour="gray40", size=baseSize-2)) + 99 | ggplot2::theme(axis.title=ggplot2::element_text(colour="gray40")) + 100 | ggplot2::theme(panel.border = ggplot2::element_rect(colour="gray80")) + 101 | ggplot2::theme(axis.ticks.length = grid::unit(0, "cm")) + 102 | ggplot2::theme(text = element_text(size =baseSize+7)) 103 | 104 | 105 | ds 106 | g <- ggplot(ds, aes(x=wave,y=y, group=id))#, color=factor(id))) 107 | g <- g + geom_line() 108 | g <- g + geom_point(shape=21, size=4, fill="purple", alpha=.5) 109 | # g <- g + geom_line(aes(y=m1_), color="red", linetype="dashed", size=2) 110 | g <- g + geom_line(aes(y=m00, color=factor(id)), linetype="dashed", size=2) 111 | g <- g + scale_y_continuous(limits=c(0,6)) 112 | g <- g + theme1 113 | g 114 | 115 | -------------------------------------------------------------------------------- /Chapters/05/R_Chapter5/SimpleExample_Key.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Chapters/05/R_Chapter5/SimpleExample_Key.xlsx -------------------------------------------------------------------------------- /Chapters/05/R_Chapter5/SimpleExample_studentCopy.R: -------------------------------------------------------------------------------- 1 | # remove all elements for a clean start 2 | rm(list=ls(all=TRUE)) 3 | cat("\014") 4 | 5 | library(dplyr) 6 | library(lme4) 7 | library(ggplot2) 8 | 9 | #### Data entry #### 10 | y <- c(2,3,2,1,2,1,5,5) 11 | id <- c(1,1,1,1,2,2,2,2) 12 | ds <- 13 | 14 | 15 | head(ds) 16 | 17 | #### Model m00 #### 18 | 19 | 20 | 21 | #### Model m01 #### 22 | 23 | 24 | 25 | #### Model m0* #### 26 | 27 | 28 | 29 | #### Model m1* #### 30 | 31 | 32 | 33 | #### Model m0 #### 34 | 35 | 36 | 37 | #### Model m0a #### 38 | 39 | 40 | 41 | 42 | #### Model m1 #### 43 | 44 | 45 | 46 | 47 | 48 | #### Graphing #### 49 | 50 | 51 | baseSize <- 12 # set as the point of further reference 52 | theme1 <- ggplot2::theme_bw(base_size=baseSize) + 53 | ggplot2::theme(title=ggplot2::element_text(colour="gray20",size = baseSize+1)) + 54 | ggplot2::theme(axis.text=ggplot2::element_text(colour="gray40", size=baseSize-2)) + 55 | ggplot2::theme(axis.title=ggplot2::element_text(colour="gray40")) + 56 | ggplot2::theme(panel.border = ggplot2::element_rect(colour="gray80")) + 57 | ggplot2::theme(axis.ticks.length = grid::unit(0, "cm")) + 58 | ggplot2::theme(text = element_text(size =baseSize+7)) 59 | 60 | 61 | ds 62 | g <- ggplot(ds, aes(x=wave,y=y, group=id))#, color=factor(id))) 63 | g <- g + geom_line() 64 | g <- g + geom_point(shape=21, size=4, fill="purple", alpha=.5) 65 | # g <- g + geom_line(aes(y=m1_), color="red", linetype="dashed", size=2) 66 | g <- g + geom_line(aes(y=m00, color=factor(id)), linetype="dashed", size=2) 67 | g <- g + scale_y_continuous(limits=c(0,6)) 68 | g <- g + theme1 69 | g 70 | 71 | -------------------------------------------------------------------------------- /Chapters/05/R_Chapter5/SimpleExample_studentCopy.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Chapters/05/R_Chapter5/SimpleExample_studentCopy.xlsx -------------------------------------------------------------------------------- /Chapters/05/R_Chapter5/figure_rmd/GraphM3_1.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Chapters/05/R_Chapter5/figure_rmd/GraphM3_1.png -------------------------------------------------------------------------------- /Chapters/05/R_Chapter5/figure_rmd/GraphM5_1.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Chapters/05/R_Chapter5/figure_rmd/GraphM5_1.png -------------------------------------------------------------------------------- /Chapters/05/R_Chapter5/figure_rmd/GraphM5_3.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Chapters/05/R_Chapter5/figure_rmd/GraphM5_3.png -------------------------------------------------------------------------------- /Chapters/05/R_Chapter5/figure_rmd/GraphM5_5.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Chapters/05/R_Chapter5/figure_rmd/GraphM5_5.png -------------------------------------------------------------------------------- /Chapters/05/R_Chapter5/figure_rmd/GraphingData0.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Chapters/05/R_Chapter5/figure_rmd/GraphingData0.png -------------------------------------------------------------------------------- /Chapters/05/R_Chapter5/figure_rmd/GraphingData1.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Chapters/05/R_Chapter5/figure_rmd/GraphingData1.png -------------------------------------------------------------------------------- /Chapters/05/R_Chapter5/figure_rmd/GraphingData2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Chapters/05/R_Chapter5/figure_rmd/GraphingData2.png -------------------------------------------------------------------------------- /Chapters/05/R_Chapter5/general.JPG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Chapters/05/R_Chapter5/general.JPG -------------------------------------------------------------------------------- /Chapters/05/R_Chapter5/how to adapt CH5 script for ELSA study.txt: -------------------------------------------------------------------------------- 1 | How to adapt "hoffman-ch5.R" to analyze ELSA data 2 | 3 | 0. Input new data, replace line 22 4 | 5 | ds0 <- readRDS("~/GitHub/psy564/Data/Derived/ELSA/dsM_ELSA.rds") 6 | 7 | 1. Add on line 44 8 | 9 | dsM <- dplyr::filter(dsM, id %in% sample(unique(id),100)) 10 | 11 | 12 | 2. Change all "PersonID" to "id" 13 | 14 | 3. Change all "outcome" to "irecall" 15 | 16 | 4. Change "limits=c(5,25)" to "limits=c(0,10)" 17 | 18 | 5. Change "breaks=seq(5,25, by=5)" to "breaks=seq(0,10, by=1)" 19 | 20 | 6. Add jitter for dots in the graphs 21 | 22 | change 23 | 24 | geom_point(size=3, shape=21, fill=NA, color="black", alpha=.6) 25 | 26 | into 27 | 28 | geom_point(size=3, shape=21, fill=NA, color="black", alpha=.6, 29 | position=position_jitter(h=.3,w=0)) 30 | 31 | 32 | 7. 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Rescale rt so Mplus will show all results 10 | rt = rt/10; 11 | time1 = session - 1; 12 | 13 | VARIABLE: 14 | NAMES = PersonID session rt; 15 | USEVARIABLES = rt time1; 16 | MISSING = ALL (-9999); 17 | CLUSTER = PersonID; 18 | WITHIN = time1; 19 | 20 | ANALYSIS: 21 | ESTIMATOR = ML; 22 | PROCESSORS = 4; 23 | TYPE = TWOLEVEL RANDOM; 24 | 25 | MODEL: 26 | 27 | %WITHIN% 28 | rt; 29 | linear | rt ON time1; 30 | 31 | %BETWEEN% 32 | [rt linear] (int btime1); 33 | rt linear; 34 | rt WITH linear; 35 | 36 | MODEL CONSTRAINT: 37 | NEW(est1-est6); 38 | ! est1: Intercept at Session=1 Time=0 39 | est1 = int*1 + btime1*0; 40 | ! est2: Intercept at Session=2 Time=1 41 | est2 = int*1 + btime1*1; 42 | ! est3: Intercept at Session=3 Time=2 43 | est3 = int*1 + btime1*2; 44 | ! est4: Intercept at Session=4 Time=3 45 | est4 = int*1 + btime1*3; 46 | ! est5: Intercept at Session=5 Time=4 47 | est5 = int*1 + btime1*4; 48 | ! est6: Intercept at Session=6 Time=5 49 | est6 = int*1 + btime1*5; 50 | -------------------------------------------------------------------------------- /Chapters/06/MPlus_Chpater6/3A R(I) R(S) F(Q).inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Ch 6: 3a: Fixed Quadratic, Random Linear Time Model 3 | 4 | DATA: 5 | FILE = MPLUS_Chapter6.csv; 6 | FORMAT = FREE; 7 | 8 | DEFINE: 9 | ! Rescale rt so Mplus will show all results 10 | rt = rt/10; 11 | time1 = (session - 1)/100; 12 | time1sq = time1*time1/100; 13 | 14 | VARIABLE: 15 | NAMES = PersonID session rt; 16 | USEVARIABLES = rt time1 time1sq; 17 | MISSING = ALL (-9999); 18 | CLUSTER = PersonID; 19 | WITHIN = time1 time1sq; 20 | 21 | ANALYSIS: 22 | ESTIMATOR = ML; 23 | PROCESSORS = 4; 24 | TYPE = TWOLEVEL RANDOM; 25 | 26 | MODEL: 27 | 28 | %WITHIN% 29 | rt; 30 | linear | rt ON time1; 31 | quad | rt ON time1sq; 32 | 33 | %BETWEEN% 34 | [rt linear quad] (int btime1 btime1sq); 35 | rt linear quad@0; 36 | rt WITH linear; 37 | 38 | MODEL CONSTRAINT: 39 | NEW(est1-est12); 40 | ! est1: Intercept at Session=1 Time=0 41 | est1 = int*1 + btime1*0 + btime1sq*0; 42 | ! est2: Intercept at Session=2 Time=1 43 | est2 = int*1 + btime1*1 + btime1sq*1; 44 | ! est3: Intercept at Session=3 Time=2 45 | est3 = int*1 + btime1*2 + btime1sq*4; 46 | ! est4: Intercept at Session=4 Time=3 47 | est4 = int*1 + btime1*3 + btime1sq*9; 48 | ! est5: Intercept at Session=5 Time=4 49 | est5 = int*1 + btime1*4 + btime1sq*16; 50 | ! est6: Intercept at Session=6 Time=5 51 | est6 = int*1 + btime1*5 + btime1sq*25; 52 | ! est7: Linear Slope at Session=1 Time=0 53 | est7 = btime1*1 + btime1sq*0; 54 | ! est8: Linear Slope at Session=2 Time=1 55 | est8 = btime1*1 + btime1sq*2; 56 | ! est9: Linear Slope at Session=3 Time=2 57 | est9 = btime1*1 + btime1sq*4; 58 | ! est10: Linear Slope at Session=4 Time=3 59 | est10 = btime1*1 + btime1sq*6; 60 | ! est11: Linear Slope at Session=5 Time=4 61 | est11 = btime1*1 + btime1sq*8; 62 | ! est12: Linear Slope at Session=6 Time=5 63 | est12 = btime1*1 + btime1sq*10; 64 | -------------------------------------------------------------------------------- /Chapters/06/SAS_Chapter6/SAS_Chapter6.sas7bdat: -------------------------------------------------------------------------------- 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-------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Data/Raw/ELSA/ds0_ELSA.rds -------------------------------------------------------------------------------- /Data/Raw/ELSA/dsELSA.rds: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Data/Raw/ELSA/dsELSA.rds -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/ELSA_report.Rmd: -------------------------------------------------------------------------------- 1 | --- 2 | title: "Reporting Statistical Models (demo)" 3 | author: "Psyc 564" 4 | date: "Friday, January 30, 2015" 5 | output: 6 | html_document: 7 | css: ~/GitHub/psy564/libs/css/sidebar.css 8 | highlight: haddock 9 | theme: spacelab 10 | toc: yes 11 | --- 12 | 13 | 14 | ```{r, echo=F, message=F} 15 | library(knitr) 16 | opts_knit$set(root.dir='../../../') #Don't combine this call with any other chunk -especially one that uses file paths. 17 | ``` 18 | 19 | 20 | ```{r, echo=F, message=T} 21 | require(knitr) 22 | opts_chunk$set( 23 | results='show', 24 | message = TRUE, 25 | comment = NA, 26 | tidy = FALSE, 27 | # fig.height = 4.8, 28 | # fig.width = 6.5, 29 | out.width = NULL, 30 | fig.path = 'figure_rmd/', 31 | dev = "png", 32 | dpi = 70 33 | ) 34 | echoChunks <- FALSE 35 | warningChunks<- FALSE 36 | messageChunks<- FALSE 37 | outwidthChunks <- "130%" 38 | options(width=120) #So the output is 50% wider than the default. 39 | read_chunk("./Projects/ELSA/CogDecline/dsELSA.R") # the file to which knitr calls for the chunks 40 | ``` 41 | 42 | ## LoadPackages 43 | ```{r LoadPackages} 44 | 45 | ``` 46 | 47 | 48 | ## Load data 49 | ```{r LoadData} 50 | 51 | ``` 52 | 53 | 54 | ## DataFilter 55 | ```{r DataFilter} 56 | 57 | ``` 58 | 59 | 60 | ## DataFilter2 61 | ```{r DataFilter2} 62 | 63 | ``` 64 | 65 | ## DataExportLong 66 | ```{r DataExportLong, eval=F} 67 | 68 | ``` 69 | 70 | ## DataExportWide 71 | ```{r DataExportWide, eval=F,echo=F} 72 | 73 | ``` 74 | NOTE: the export of the wide data is suppressed for brevity 75 | 76 | ## LoadGraphThemes 77 | ```{r LoadGraphThemes} 78 | 79 | ``` 80 | 81 | ## CrossSectionDist 82 | ```{r CrossSectionDist, out.width="900px"} 83 | 84 | ``` 85 | 86 | ## CrossSectionCount 87 | ```{r CrossSectionCount, out.width="900px"} 88 | 89 | ``` 90 | 91 | ## MakeAgeBins 92 | ```{r MakeAgeBins} 93 | 94 | ``` 95 | 96 | ## EasyData 97 | ```{r EasyData} 98 | 99 | ``` 100 | 101 | ## BasicLinePlot 102 | ```{r BasicLinePlot, warning=F,out.width="900px"} 103 | 104 | ``` 105 | 106 | ## DefineModelData 107 | ```{r DefineModelData, warning=F} 108 | 109 | ``` 110 | 111 | ## ProtoLines 112 | ```{r ProtoLines, warning=F} 113 | 114 | ``` 115 | 116 | ## IndividualPredictionsAge 117 | ```{r IndividualPredictionsAge, warning=F, out.width="900px"} 118 | 119 | ``` 120 | 121 | 122 | 123 | ## DefineModelData2 124 | ```{r DefineModelData2, warning=F} 125 | 126 | ``` 127 | 128 | ## ProtoLines2 129 | ```{r ProtoLines2, warning=F} 130 | 131 | ``` 132 | 133 | ## IndividualPredictionsAge2 134 | ```{r IndividualPredictionsAge2, warning=F} 135 | 136 | ``` 137 | 138 | 139 | 140 | 141 | 142 | 143 | 144 | 145 | 146 | 147 | 148 | 149 | 150 | 151 | 152 | 153 | 154 | 155 | 156 | 157 | 158 | 159 | 160 | -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/dsL_ELSA_varNames.csv: -------------------------------------------------------------------------------- 1 | "","V1","V2","V3","V4","V5","V6","V7","V8","V9","V10","V11","V12","V13","V14","V15","V16","V17","V18","V19","V20","V21","V22","V23","V24","V25","V26","V27","V28","V29","V30","V31","V32" 2 | "1","id","dob","sex","age","edu","ht","db","htdb","nocase","ang1A","chf1A","mi1A","stk1A","cogflg1A","evrsmk1A","htnw1A","dmw1A","time","irecall","animal","prospect","drecall","age80","edu11","hptn","dbts","condition","wave","year","Age","waveF","female" 3 | -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/dsW_ELSA_varNames.csv: -------------------------------------------------------------------------------- 1 | "","V1","V2","V3","V4","V5","V6","V7","V8","V9","V10","V11","V12","V13","V14","V15","V16","V17","V18","V19","V20","V21","V22","V23","V24","V25","V26","V27","V28","V29","V30","V31","V32","V33","V34","V35","V36","V37","V38","V39","V40","V41","V42","V43","V44" 2 | "1","id","dob","sex","age","edu","ht","db","htdb","nocase","angina","stroke","smoked","time_1","time_2","time_3","time_4","wave_1","wave_2","wave_3","wave_4","year_1","year_2","year_3","year_4","ageCur_1","ageCur_2","ageCur_3","ageCur_4","irecall_1","irecall_2","irecall_3","irecall_4","drecall_1","drecall_2","drecall_3","drecall_4","animal_1","animal_2","animal_3","animal_4","prospect_1","prospect_2","prospect_3","prospect_4" 3 | -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/extract from mplus.R: -------------------------------------------------------------------------------- 1 | # remove all elements for a clean start 2 | rm(list=ls(all=TRUE)) 3 | cat("\014") 4 | 5 | ## @knitr LoadPackages 6 | require(sas7bdat) # for inputting data 7 | library(dplyr) # for general data manipulation 8 | library(reshape2) # for data : wide <-> long 9 | library(psych) # data summary + etc 10 | library(ggplot2) # graphing 11 | library(nlme) # estimate fixed models | esp. gls() 12 | library(lme4) # estimate mixed models | esp. lmer() 13 | library(arm) # process model objects 14 | 15 | # source("./Scripts/Mplus/mplus.R") 16 | source("http://www.statmodel.com/mplus-R/mplus.R") 17 | ls() # list the availible function in mplus.R 18 | 19 | m0 <- "./Projects/ELSA/CogDecline/irecall/irecall_r(i)_r(s)_nocovar.gh5" 20 | m1 <- "./Projects/ELSA/CogDecline/irecall/irecall_r(i)_r(s)_(is)age80.gh5" 21 | m2 <- "./Projects/ELSA/CogDecline/irecall/irecall_r(i)_r(s)_(is)age80_(is)edu11.gh5" 22 | m3 <- "./Projects/ELSA/CogDecline/irecall/irecall_r(i)_r(s)_(is)age80_(is)edu11_(is)smoked.gh5" 23 | 24 | 25 | mplus.view.plots(m3) 26 | model <- m3 27 | 28 | mplus.list.variables(m3) 29 | 30 | mplus.plot.histogram(model, "OUTCOME") 31 | mplus.plot.histogram(model, "TIMEL") 32 | mplus.plot.histogram(model, "EVRSMK1A") 33 | mplus.plot.histogram(model, "EDU11") 34 | mplus.plot.histogram(model, "AGE80") 35 | mplus.plot.histogram(model, "LINEAR") 36 | mplus.plot.histogram(model, "B_OUTCOME") 37 | 38 | # extract raw data 39 | a <- mplus.get.data(m2,"OUTCOME") 40 | b <- mplus.get.data(m2,"TIMEL") 41 | c <- mplus.get.data(m2,"EDU11") 42 | d <- mplus.get.data(m2,"AGE80") 43 | e <- mplus.get.data(m2,"LINEAR") 44 | f <- mplus.get.data(m2,"B_OUTCOME") 45 | g <- mplus.get.data(m2,"ID") 46 | 47 | ds <- data.frame(cbind(a, b, c, d, e, f, g)) 48 | names(ds) <- c("OUTCOME", "TIMEL","EDU11","AGE80","LINEAR","B_OUTCOME","ID") 49 | 50 | head(ds) 51 | 52 | 53 | 54 | ###### ######## 55 | mplus.load(m1) 56 | mplus.plot.loop(m1, ypred) 57 | 58 | source("http://www.statmodel.com/mplus-R/mplus.R") 59 | ls() # list the availible function in mplus.R 60 | 61 | # create objects containing the paths to gh5 files 62 | model_basic <- './Projects/HRS/Various/HRS_BASIC.gh5' 63 | model_growth <- './Projects/HRS/Various/hrs_lgmgrowth.gh5' 64 | 65 | # choose what model to work with 66 | model <- model_basic 67 | model <- model_growth 68 | 69 | 70 | 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https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Projects/ELSA/CogDecline/figure_rmd/ProtoLines2-1.png -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/irecall/irecall_r(I)_r(S)_(IS)Age80.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Modeling Cognitive Decline in ELSA study: irecall 3 | 4 | DATA: 5 | FILE = dsL_ELSA.csv; 6 | FORMAT = FREE; 7 | 8 | DEFINE: 9 | ! choose the metric of time 10 | timeL = wave - 1; 11 | ! choose the outcome 12 | outcome = irecall; 13 | 14 | !123456789!123456789!123456789!123456789!123456789!123456789!123456789!123456789! 15 | VARIABLE: 16 | NAMES = id dob sex age1B edu ht db htdb nocase ang1A chf1A mi1A stk1A cogflg1A 17 | evrsmk1A htnw1A dmw1A timeToIn irecall animal prospect drecall age80 edu11 hptn 18 | dbts condition wave year Age waveF female; 19 | USEVARIABLES = age80 outcome timeL ; 20 | MISSING = ALL (-9999); 21 | CLUSTER = id; 22 | WITHIN = timeL; 23 | BETWEEN = age80; 24 | 25 | 26 | 27 | ANALYSIS: 28 | ESTIMATOR = ML; 29 | PROCESSORS = 4; 30 | TYPE = TWOLEVEL RANDOM; 31 | 32 | MODEL: 33 | 34 | %WITHIN% 35 | outcome; 36 | linear | outcome ON timeL; 37 | 38 | %BETWEEN% 39 | [outcome linear ] (int btimeL ); 40 | outcome linear ; 41 | outcome WITH linear ; 42 | outcome linear ON age80 ; 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/irecall/irecall_r(I)_r(S)_(IS)Age80_(IS)Edu11.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Modeling Cognitive Decline in ELSA study: irecall 3 | 4 | DATA: 5 | FILE = dsL_ELSA.csv; 6 | FORMAT = FREE; 7 | 8 | DEFINE: 9 | ! choose the metric of time 10 | timeL = wave - 1; 11 | ! choose the outcome 12 | outcome = irecall; 13 | 14 | !123456789!123456789!123456789!123456789!123456789!123456789!123456789!123456789! 15 | VARIABLE: 16 | NAMES = id dob sex age1B edu ht db htdb nocase ang1A chf1A mi1A stk1A cogflg1A 17 | evrsmk1A htnw1A dmw1A timeToIn irecall animal prospect drecall age80 edu11 hptn 18 | dbts condition wave year Age waveF female; 19 | USEVARIABLES = edu11 age80 outcome timeL ; 20 | MISSING = ALL (-9999); 21 | CLUSTER = id; 22 | WITHIN = timeL; 23 | BETWEEN = edu11 age80; 24 | 25 | 26 | 27 | ANALYSIS: 28 | ESTIMATOR = ML; 29 | PROCESSORS = 4; 30 | TYPE = TWOLEVEL RANDOM; 31 | 32 | MODEL: 33 | 34 | %WITHIN% 35 | outcome; 36 | linear | outcome ON timeL; 37 | 38 | %BETWEEN% 39 | [outcome linear ] (int btimeL ); 40 | outcome linear ; 41 | outcome WITH linear ; 42 | outcome linear ON age80 ; 43 | outcome linear ON edu11 ; 44 | 45 | PLOT: 46 | type = plot1; 47 | type = plot2; 48 | type = plot3; 49 | 50 | 51 | 52 | 53 | 54 | -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/irecall/irecall_r(I)_r(S)_(IS)Age80_(IS)Edu11_(IS)Smoked.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Modeling Cognitive Decline in ELSA study: irecall 3 | 4 | DATA: 5 | FILE = dsL_ELSA.csv; 6 | FORMAT = FREE; 7 | 8 | DEFINE: 9 | ! choose the metric of time 10 | timeL = wave - 1; 11 | ! choose the outcome 12 | outcome = irecall; 13 | 14 | !123456789!123456789!123456789!123456789!123456789!123456789!123456789!123456789! 15 | VARIABLE: 16 | NAMES = id dob sex age1B edu ht db htdb nocase ang1A chf1A mi1A stk1A cogflg1A 17 | evrsmk1A htnw1A dmw1A timeToIn irecall animal prospect drecall age80 edu11 hptn 18 | dbts condition wave year Age waveF female; 19 | USEVARIABLES = evrsmk1A edu11 age80 outcome timeL ; 20 | MISSING = ALL (-9999); 21 | CLUSTER = id; 22 | WITHIN = timeL; 23 | BETWEEN = evrsmk1A edu11 age80; 24 | 25 | 26 | 27 | ANALYSIS: 28 | ESTIMATOR = ML; 29 | PROCESSORS = 4; 30 | TYPE = TWOLEVEL RANDOM; 31 | 32 | MODEL: 33 | 34 | %WITHIN% 35 | outcome; 36 | linear | outcome ON timeL; 37 | 38 | %BETWEEN% 39 | [outcome linear ] (int btimeL ); 40 | outcome linear ; 41 | outcome WITH linear ; 42 | outcome linear ON age80 ; 43 | outcome linear ON edu11 ; 44 | outcome linear ON evrsmk1A ; 45 | 46 | PLOT: 47 | type = plot1; 48 | type = plot2; 49 | type = plot3; 50 | 51 | 52 | 53 | 54 | 55 | -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/irecall/irecall_r(I)_r(S)_NoCovar.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Modeling Cognitive Decline in ELSA study: irecall 3 | 4 | DATA: 5 | FILE = dsL_ELSA.csv; 6 | FORMAT = FREE; 7 | 8 | DEFINE: 9 | ! choose the metric of time 10 | timeL = wave - 1; 11 | ! choose the outcome 12 | outcome = irecall; 13 | 14 | !123456789!123456789!123456789!123456789!123456789!123456789!123456789!123456789! 15 | VARIABLE: 16 | NAMES = id dob sex age1B edu ht db htdb nocase ang1A chf1A mi1A stk1A cogflg1A 17 | evrsmk1A htnw1A dmw1A timeToIn irecall animal prospect drecall age80 edu11 hptn 18 | dbts condition wave year Age waveF female; 19 | USEVARIABLES = outcome timeL ; 20 | MISSING = ALL (-9999); 21 | CLUSTER = id; 22 | WITHIN = timeL; 23 | ! BETWEEN = age80; 24 | 25 | 26 | 27 | ANALYSIS: 28 | ESTIMATOR = ML; 29 | PROCESSORS = 4; 30 | TYPE = TWOLEVEL RANDOM; 31 | 32 | MODEL: 33 | 34 | %WITHIN% 35 | outcome; 36 | linear | outcome ON timeL; 37 | 38 | %BETWEEN% 39 | [outcome linear ] (int btimeL ); 40 | outcome linear ; 41 | outcome WITH linear ; 42 | 43 | OUTPUT: TECH1 TECH8; 44 | !PLOT: 45 | ! TYPE = plot2; 46 | ! SERIES = outcome(*) ; 47 | 48 | !MODEL CONSTRAINT: 49 | ! PLOT (ypred); 50 | ! LOOP (age80,-10,10,1) : 51 | ! ypred = btimeL*age80; 52 | 53 | !SAVEDATA: FSCORES ; 54 | 55 | 56 | 57 | -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/irecall/irecall_r(i)_r(s)_(is)age80.gh5: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Projects/ELSA/CogDecline/irecall/irecall_r(i)_r(s)_(is)age80.gh5 -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/irecall/irecall_r(i)_r(s)_(is)age80_(is)edu11.gh5: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Projects/ELSA/CogDecline/irecall/irecall_r(i)_r(s)_(is)age80_(is)edu11.gh5 -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/irecall/irecall_r(i)_r(s)_(is)age80_(is)edu11_(is)smoked.gh5: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Projects/ELSA/CogDecline/irecall/irecall_r(i)_r(s)_(is)age80_(is)edu11_(is)smoked.gh5 -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/irecall/irecall_r(i)_r(s)_nocovar.gh5: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Projects/ELSA/CogDecline/irecall/irecall_r(i)_r(s)_nocovar.gh5 -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/irecall/results.dat: -------------------------------------------------------------------------------- 1 | 0.15629333E+01 -0.19000806E-01 0.58720625E+01 0.92817729E-02 0.52573595E-01 0.90631180E+00 2 | 0.21012824E-01 0.76298482E-02 0.24247442E-01 0.74243829E-02 0.19889780E-01 0.69388549E-01 3 | -0.40299902E+05 0.60000000E+01 0.80611803E+05 0.80659828E+05 0.80640760E+05 4 | -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/irecall/retired/irecall_0r_1f_2x_x.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Modeling Cognitive Decline in ELSA study: irecall 3 | 4 | DATA: 5 | FILE = dsL_ELSA.csv; 6 | FORMAT = FREE; 7 | 8 | DEFINE: 9 | ! choose the metric of time 10 | timeL = wave; 11 | ! timeQ = wave*wave; 12 | ! choose the outcome 13 | outcome = irecall; 14 | 15 | !123456789!123456789!123456789!123456789!123456789!123456789!123456789!123456789! 16 | VARIABLE: 17 | NAMES = id dob sex age1B edu ht db htdb nocase ang1A chf1A mi1A stk1A cogflg1A 18 | evrsmk1A htnw1A dmw1A timeToIn irecall animal prospect drecall age80 edu11 hptn 19 | dbts condition wave year Age waveF female; 20 | USEVARIABLES = outcome timeL; 21 | MISSING = ALL (-9999); 22 | CLUSTER = id; 23 | WITHIN = timeL ; 24 | 25 | 26 | 27 | ANALYSIS: 28 | ESTIMATOR = ML; 29 | PROCESSORS = 4; 30 | TYPE = TWOLEVEL RANDOM; 31 | 32 | MODEL: 33 | 34 | %WITHIN% 35 | outcome; 36 | linear | outcome on timeL; 37 | 38 | 39 | %BETWEEN% 40 | [outcome linear] (int btimeL); 41 | outcome linear@0; 42 | 43 | 44 | 45 | 46 | -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/irecall/retired/irecall_r0_r1_f2_x.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Modeling Cognitive Decline in ELSA study: irecall 3 | 4 | DATA: 5 | FILE = dsL_ELSA.csv; 6 | FORMAT = FREE; 7 | 8 | DEFINE: 9 | ! choose the metric of time 10 | timeL = wave; 11 | timeQ = wave*wave; 12 | ! choose the outcome 13 | outcome = irecall; 14 | 15 | !123456789!123456789!123456789!123456789!123456789!123456789!123456789!123456789! 16 | VARIABLE: 17 | NAMES = id dob sex age1B edu ht db htdb nocase ang1A chf1A mi1A stk1A cogflg1A 18 | evrsmk1A htnw1A dmw1A timeToIn irecall animal prospect drecall age80 edu11 hptn 19 | dbts condition wave year Age waveF female; 20 | USEVARIABLES = outcome timeL timeQ; 21 | MISSING = ALL (-9999); 22 | CLUSTER = id; 23 | WITHIN = timeL timeQ; 24 | 25 | 26 | 27 | ANALYSIS: 28 | ESTIMATOR = ML; 29 | PROCESSORS = 4; 30 | TYPE = TWOLEVEL RANDOM; 31 | 32 | MODEL: 33 | 34 | %WITHIN% 35 | outcome; 36 | linear | outcome ON timeL; 37 | quad | outcome ON timeQ; 38 | 39 | 40 | %BETWEEN% 41 | [outcome linear quad] (int btimeL btimeQ); 42 | outcome linear quad@0; 43 | outcome WITH linear; 44 | 45 | 46 | 47 | 48 | -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/irecall/retired/irecall_r0_r1_r2_012age80.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Modeling Cognitive Decline in ELSA study: irecall 3 | 4 | DATA: 5 | FILE = dsL_ELSA.csv; 6 | FORMAT = FREE; 7 | 8 | DEFINE: 9 | ! choose the metric of time 10 | timeL = wave; 11 | timeQ = wave*wave; 12 | ! choose the outcome 13 | outcome = irecall; 14 | 15 | !123456789!123456789!123456789!123456789!123456789!123456789!123456789!123456789! 16 | VARIABLE: 17 | NAMES = id dob sex age1B edu ht db htdb nocase ang1A chf1A mi1A stk1A cogflg1A 18 | evrsmk1A htnw1A dmw1A timeToIn irecall animal prospect drecall age80 edu11 hptn 19 | dbts condition wave year Age waveF female; 20 | USEVARIABLES = age80 outcome timeL timeQ; 21 | MISSING = ALL (-9999); 22 | CLUSTER = id; 23 | WITHIN = timeL timeQ; 24 | BETWEEN = age80; 25 | 26 | 27 | 28 | ANALYSIS: 29 | ESTIMATOR = ML; 30 | PROCESSORS = 4; 31 | TYPE = TWOLEVEL RANDOM; 32 | 33 | MODEL: 34 | 35 | %WITHIN% 36 | outcome; 37 | linear | outcome ON timeL; 38 | quad | outcome ON timeQ; 39 | 40 | 41 | %BETWEEN% 42 | [outcome linear quad] (int btimeL btimeQ); 43 | outcome linear quad; 44 | outcome linear quad WITH outcome linear quad; 45 | outcome linear quad ON age80 (bage80I bage80S bage80Q); 46 | 47 | 48 | 49 | 50 | -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/irecall/retired/irecall_r0_r1_r2_012age80_0edu11.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Modeling Cognitive Decline in ELSA study: irecall 3 | 4 | DATA: 5 | FILE = dsL_ELSA.csv; 6 | FORMAT = FREE; 7 | 8 | DEFINE: 9 | ! choose the metric of time 10 | timeL = wave; 11 | timeQ = wave*wave; 12 | ! choose the outcome 13 | outcome = irecall; 14 | 15 | !123456789!123456789!123456789!123456789!123456789!123456789!123456789!123456789! 16 | VARIABLE: 17 | NAMES = id dob sex age1B edu ht db htdb nocase ang1A chf1A mi1A stk1A cogflg1A 18 | evrsmk1A htnw1A dmw1A timeToIn irecall animal prospect drecall age80 edu11 hptn 19 | dbts condition wave year Age waveF female; 20 | USEVARIABLES = age80 edu11 outcome timeL timeQ; 21 | MISSING = ALL (-9999); 22 | CLUSTER = id; 23 | WITHIN = timeL timeQ; 24 | BETWEEN = age80 edu11; 25 | 26 | 27 | 28 | ANALYSIS: 29 | ESTIMATOR = ML; 30 | PROCESSORS = 4; 31 | TYPE = TWOLEVEL RANDOM; 32 | 33 | MODEL: 34 | 35 | %WITHIN% 36 | outcome; 37 | linear | outcome ON timeL; 38 | quad | outcome ON timeQ; 39 | 40 | %BETWEEN% 41 | [outcome linear quad] (int btimeL btimeQ); 42 | outcome linear quad; 43 | outcome linear quad WITH outcome linear quad; 44 | outcome linear quad ON age80 (bage80I bage80S bage80Q); 45 | outcome linear ON edu11 (bedu11I); 46 | 47 | 48 | 49 | 50 | -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/irecall/retired/irecall_r0_r1_r2_01age80.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Modeling Cognitive Decline in ELSA study: irecall 3 | 4 | DATA: 5 | FILE = dsL_ELSA.csv; 6 | FORMAT = FREE; 7 | 8 | DEFINE: 9 | ! choose the metric of time 10 | timeL = wave; 11 | timeQ = wave*wave; 12 | ! choose the outcome 13 | outcome = irecall; 14 | 15 | !123456789!123456789!123456789!123456789!123456789!123456789!123456789!123456789! 16 | VARIABLE: 17 | NAMES = id dob sex age1B edu ht db htdb nocase ang1A chf1A mi1A stk1A cogflg1A 18 | evrsmk1A htnw1A dmw1A timeToIn irecall animal prospect drecall age80 edu11 hptn 19 | dbts condition wave year Age waveF female; 20 | USEVARIABLES = age80 outcome timeL timeQ; 21 | MISSING = ALL (-9999); 22 | CLUSTER = id; 23 | WITHIN = timeL timeQ; 24 | BETWEEN = age80; 25 | 26 | 27 | 28 | ANALYSIS: 29 | ESTIMATOR = ML; 30 | PROCESSORS = 4; 31 | TYPE = TWOLEVEL RANDOM; 32 | 33 | MODEL: 34 | 35 | %WITHIN% 36 | outcome; 37 | linear | outcome ON timeL; 38 | quad | outcome ON timeQ; 39 | 40 | 41 | %BETWEEN% 42 | [outcome linear quad] (int btimeL btimeQ); 43 | outcome linear quad; 44 | outcome linear quad WITH outcome linear quad; 45 | outcome linear ON age80 (bage80in bage80lin); 46 | 47 | 48 | 49 | 50 | -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/irecall/retired/irecall_r0_r1_r2_0age80.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Modeling Cognitive Decline in ELSA study: irecall 3 | 4 | DATA: 5 | FILE = dsL_ELSA.csv; 6 | FORMAT = FREE; 7 | 8 | DEFINE: 9 | ! choose the metric of time 10 | timeL = wave; 11 | timeQ = wave*wave; 12 | ! choose the outcome 13 | outcome = irecall; 14 | 15 | !123456789!123456789!123456789!123456789!123456789!123456789!123456789!123456789! 16 | VARIABLE: 17 | NAMES = id dob sex age1B edu ht db htdb nocase ang1A chf1A mi1A stk1A cogflg1A 18 | evrsmk1A htnw1A dmw1A timeToIn irecall animal prospect drecall age80 edu11 hptn 19 | dbts condition wave year Age waveF female; 20 | USEVARIABLES = age80 outcome timeL timeQ; 21 | MISSING = ALL (-9999); 22 | CLUSTER = id; 23 | WITHIN = timeL timeQ; 24 | BETWEEN = age80; 25 | 26 | 27 | 28 | ANALYSIS: 29 | ESTIMATOR = ML; 30 | PROCESSORS = 4; 31 | TYPE = TWOLEVEL RANDOM; 32 | 33 | MODEL: 34 | 35 | %WITHIN% 36 | outcome; 37 | linear | outcome ON timeL; 38 | quad | outcome ON timeQ; 39 | 40 | 41 | %BETWEEN% 42 | [outcome linear quad] (int btimeL btimeQ); 43 | outcome linear quad; 44 | outcome linear quad WITH outcome linear quad; 45 | outcome ON age80 (bage80); 46 | 47 | 48 | 49 | 50 | -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/irecall/retired/irecall_r0_r1_r2_age012.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Modeling Cognitive Decline in ELSA study: irecall 3 | 4 | DATA: 5 | FILE = dsL_ELSA.csv; 6 | FORMAT = FREE; 7 | 8 | DEFINE: 9 | linear = wave; 10 | quad = wave*wave; 11 | y = irecall; 12 | 13 | 14 | !123456789!123456789!123456789!123456789!123456789!123456789!123456789!123456789! 15 | VARIABLE: 16 | NAMES = id dob sex age1B edu ht db htdb nocase ang1A chf1A mi1A stk1A cogflg1A 17 | evrsmk1A htnw1A dmw1A time irecall animal prospect drecall age80 edu11 hptn 18 | dbts condition wave year Age waveF female; 19 | USEVARIABLES = id age80 y linear quad; 20 | MISSING = ALL (NA); 21 | CLUSTER = id; 22 | WITHIN = linear quad; 23 | 24 | ANALYSIS: 25 | ESTIMATOR = ML; 26 | PROCESSORS = 4; 27 | TYPE = TWOLEVEL RANDOM; 28 | 29 | MODEL: 30 | 31 | %WITHIN% 32 | y; 33 | linear | y ON age80; 34 | quad | y ON age80; 35 | 36 | %BETWEEN% 37 | [y linear quad] (int bagec18 bagesq); 38 | y linear quad; 39 | y linear quad WITH y linear quad; 40 | 41 | 42 | -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/irecall/retired/irecall_r0_r1_r2_age012.out: -------------------------------------------------------------------------------- 1 | Mplus VERSION 7.3 2 | MUTHEN & MUTHEN 3 | 03/06/2015 10:10 AM 4 | 5 | INPUT INSTRUCTIONS 6 | 7 | TITLE: 8 | Modeling Cognitive Decline in ELSA study: irecall 9 | 10 | DATA: 11 | FILE = dsL_ELSA.csv; 12 | FORMAT = FREE; 13 | 14 | DEFINE: 15 | linear = wave; 16 | quad = wave*wave; 17 | y = irecall; 18 | 19 | 20 | !123456789!123456789!123456789!123456789!123456789!123456789!123456789!123456789! 21 | VARIABLE: 22 | NAMES = id dob sex age1B edu ht db htdb nocase ang1A chf1A mi1A stk1A cogflg1A 23 | evrsmk1A htnw1A dmw1A time irecall animal prospect drecall age80 edu11 hptn 24 | dbts condition wave year Age waveF female; 25 | USEVARIABLES = id age80 y linear quad; 26 | MISSING = ALL (NA); 27 | CLUSTER = id; 28 | WITHIN = linear quad; 29 | 30 | ANALYSIS: 31 | ESTIMATOR = ML; 32 | PROCESSORS = 4; 33 | TYPE = TWOLEVEL RANDOM; 34 | 35 | MODEL: 36 | 37 | %WITHIN% 38 | y; 39 | linear | y ON age80; 40 | quad | y ON age80; 41 | 42 | %BETWEEN% 43 | [y linear quad] (int bagec18 bagesq); 44 | y linear quad; 45 | y linear quad WITH y linear quad; 46 | 47 | 48 | 49 | *** ERROR 50 | Invalid missing value: NA 51 | 52 | 53 | MUTHEN & MUTHEN 54 | 3463 Stoner Ave. 55 | Los Angeles, CA 90066 56 | 57 | Tel: (310) 391-9971 58 | Fax: (310) 391-8971 59 | Web: www.StatModel.com 60 | Support: Support@StatModel.com 61 | 62 | Copyright (c) 1998-2014 Muthen & Muthen 63 | -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/irecall/retired/irecall_r0_r1_r2_x.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Modeling Cognitive Decline in ELSA study: irecall 3 | 4 | DATA: 5 | FILE = dsL_ELSA.csv; 6 | FORMAT = FREE; 7 | 8 | DEFINE: 9 | ! choose the metric of time 10 | timeL = wave; 11 | timeQ = wave*wave; 12 | ! choose the outcome 13 | outcome = irecall; 14 | 15 | !123456789!123456789!123456789!123456789!123456789!123456789!123456789!123456789! 16 | VARIABLE: 17 | NAMES = id dob sex age1B edu ht db htdb nocase ang1A chf1A mi1A stk1A cogflg1A 18 | evrsmk1A htnw1A dmw1A timeToIn irecall animal prospect drecall age80 edu11 hptn 19 | dbts condition wave year Age waveF female; 20 | USEVARIABLES = outcome timeL timeQ; 21 | MISSING = ALL (-9999); 22 | CLUSTER = id; 23 | WITHIN = timeL timeQ; 24 | 25 | 26 | 27 | ANALYSIS: 28 | ESTIMATOR = ML; 29 | PROCESSORS = 4; 30 | TYPE = TWOLEVEL RANDOM; 31 | 32 | MODEL: 33 | 34 | %WITHIN% 35 | outcome; 36 | linear | outcome ON timeL; 37 | quad | outcome ON timeQ; 38 | 39 | 40 | %BETWEEN% 41 | [outcome linear quad] (int btimeL btimeQ); 42 | outcome linear quad; 43 | outcome linear quad WITH outcome linear quad; 44 | 45 | 46 | 47 | 48 | -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/irecall/retired/irecall_r0_r1_x2_x.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Modeling Cognitive Decline in ELSA study: irecall 3 | 4 | DATA: 5 | FILE = dsL_ELSA.csv; 6 | FORMAT = FREE; 7 | 8 | DEFINE: 9 | ! choose the metric of time 10 | timeL = wave; 11 | ! timeQ = wave*wave; 12 | ! choose the outcome 13 | outcome = irecall; 14 | 15 | !123456789!123456789!123456789!123456789!123456789!123456789!123456789!123456789! 16 | VARIABLE: 17 | NAMES = id dob sex age1B edu ht db htdb nocase ang1A chf1A mi1A stk1A cogflg1A 18 | evrsmk1A htnw1A dmw1A timeToIn irecall animal prospect drecall age80 edu11 hptn 19 | dbts condition wave year Age waveF female; 20 | USEVARIABLES = outcome timeL; 21 | MISSING = ALL (-9999); 22 | CLUSTER = id; 23 | WITHIN = timeL ; 24 | 25 | 26 | 27 | ANALYSIS: 28 | ESTIMATOR = ML; 29 | PROCESSORS = 4; 30 | TYPE = TWOLEVEL RANDOM; 31 | 32 | MODEL: 33 | 34 | %WITHIN% 35 | outcome; 36 | linear | outcome on timeL; 37 | 38 | 39 | %BETWEEN% 40 | [outcome linear] (int btimeL); 41 | outcome linear; 42 | outcome WITH linear; 43 | 44 | 45 | 46 | 47 | -------------------------------------------------------------------------------- /Projects/ELSA/CogDecline/irecall/retired/irecall_r0_x1_x2_x.inp: -------------------------------------------------------------------------------- 1 | TITLE: 2 | Modeling Cognitive Decline in ELSA study: irecall 3 | 4 | DATA: 5 | FILE = dsL_ELSA.csv; 6 | FORMAT = FREE; 7 | 8 | DEFINE: 9 | ! choose the metric of time 10 | ! timeL = wave; 11 | ! timeQ = wave*wave; 12 | ! choose the outcome 13 | outcome = irecall; 14 | 15 | !123456789!123456789!123456789!123456789!123456789!123456789!123456789!123456789! 16 | VARIABLE: 17 | NAMES = id dob sex age1B edu ht db htdb nocase ang1A chf1A mi1A stk1A cogflg1A 18 | evrsmk1A htnw1A dmw1A timeToIn irecall animal prospect drecall age80 edu11 hptn 19 | dbts condition wave year Age waveF female; 20 | USEVARIABLES = id outcome ; 21 | MISSING = ALL (-9999); 22 | CLUSTER = id; 23 | ! WITHIN = timeL ; 24 | 25 | 26 | 27 | ANALYSIS: 28 | ESTIMATOR = ML; 29 | PROCESSORS = 4; 30 | TYPE = TWOLEVEL RANDOM; 31 | 32 | MODEL: 33 | 34 | %WITHIN% 35 | outcome; 36 | 37 | 38 | %BETWEEN% 39 | [outcome] ; 40 | 41 | 42 | 43 | 44 | -------------------------------------------------------------------------------- /Projects/HRS/HRS.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Projects/HRS/HRS.zip -------------------------------------------------------------------------------- /Projects/HRS/Various/HRS_BASIC.inp: -------------------------------------------------------------------------------- 1 | Title: HRS_WIDE_BASIC; 2 | Data: 3 | File is HRS_WIDE_n2000.dat ; 4 | Variable: 5 | Names are 6 | secu idstrat idstudy idcohort 7 | wgtr4 wgtr5 wgtr6 wgtr7 wgtr8 wgtrbase wgt_pos 8 | 9 | ddobmth ddobyr dndimtch dndimth dndiyr ddodyrs ddthflg dfrstint 10 | dintmth4 dintmth5 dintmth6 dintmth7 dintmth8 11 | dsex dedudgr deduyrs 12 | dracehsp dracecnt dracewht draceblk draceoth 13 | 14 | dageyrs4 dageyrs5 dageyrs6 dageyrs7 dageyrs8 15 | dagecnt4 dagecnt5 dagecnt6 dagecnt7 dagecnt8 16 | dagesqr4 dagesqr5 dagesqr6 dagesqr7 dagesqr8 17 | dagec2_4 dagec2_5 dagec2_6 dagec2_7 dagec2_8 18 | 19 | dhhsize4 dhhsize5 dhhsize6 dhhsize7 dhhsize8 20 | dmarint4 dmarint5 dmarint6 dmarint7 dmarint8 21 | ewthfin4 ewthfin5 ewthfin6 ewthfin7 ewthfin8 22 | eincind4 einchh4 eincind5 einchh5 eincind6 einchh6 23 | eincind7 einchh7 eincind8 einchh8 24 | 25 | bexcfrq4 bexcfrq5 bexcfrq6 bexcfrq7 bexcfrq8 26 | bsmkevr4 bsmkevr5 bsmkevr6 bsmkevr7 bsmkevr8 27 | bsmknow4 bsmknow5 bsmknow6 bsmknow7 bsmknow8 28 | balcevr4 balcevr5 balcevr6 balcevr7 balcevr8 29 | balcdwk4 balcdwk5 balcdwk6 balcdwk7 balcdwk8 30 | balcddy4 balcddy5 balcddy6 balcddy7 balcddy8 31 | 32 | hvtlsts4 hvtlsts5 hvtlsts6 hvtlsts7 hvtlsts8 33 | hbmi4 hbmi5 hbmi6 hbmi7 hbmi8 34 | hsrhscr4 hsrhscr5 hsrhscr6 hsrhscr7 hsrhscr8 35 | hbrkhip4 hbrkhip5 hbrkhip6 hbrkhip7 hbrkhip8 36 | hbcksym4 hbcksym5 hbcksym6 hbcksym7 hbcksym8 37 | hhbpdia4 hhbpdia5 hhbpdia6 hhbpdia7 hhbpdia8 38 | hdibdia4 hdibdia5 hdibdia6 hdibdia7 hdibdia8 39 | hcandia4 hcandia5 hcandia6 hcandia7 hcandia8 40 | hlngdia4 hlngdia5 hlngdia6 hlngdia7 hlngdia8 41 | hpsydia4 hpsydia5 hpsydia6 hpsydia7 hpsydia8 42 | hartdia4 hartdia5 hartdia6 hartdia7 hartdia8 43 | hstkdia4 hstkdia5 hstkdia6 hstkdia7 hstkdia8 44 | hhrtdia4 hhrtdia5 hhrtdia6 hhrtdia7 hhrtdia8 45 | hiad3pt4 hiad3pt5 hiad3pt6 hiad3pt7 hiad3pt8 46 | hiad5pt4 hiad5pt5 hiad5pt6 hiad5pt7 hiad5pt8 47 | hadl3pt4 hadl3pt5 hadl3pt6 hadl3pt7 hadl3pt8 48 | hadl5pt4 hadl5pt5 hadl5pt6 hadl5pt7 hadl5pt8 49 | 50 | pcsdsum4 pcsdsum5 pcsdsum6 pcsdsum7 pcsdsum8 51 | csrmscr4 csrmscr5 csrmscr6 csrmscr7 csrmscr8 52 | cticlow4 cticlow5 cticlow6 cticlow7 cticlow8 53 | ctic9pt4 ctic9pt5 ctic9pt6 ctic9pt7 ctic9pt8 54 | ciwrstd4 ciwrstd5 ciwrstd6 ciwrstd7 ciwrstd8 55 | cdwrstd4 cdwrstd5 cdwrstd6 cdwrstd7 cdwrstd8 56 | ciwrscr4 ciwrscr5 ciwrscr6 ciwrscr7 ciwrscr8 57 | cdwrscr4 cdwrscr5 cdwrscr6 cdwrscr7 cdwrscr8 58 | cssstd4 cssstd5 cssstd6 cssstd7 cssstd8 59 | cssscr4 cssscr5 cssscr6 cssscr7 cssscr8 60 | cvcbstd4 cvcbstd5 cvcbstd6 cvcbstd7 cvcbstd8 61 | cvcbscr4 cvcbscr5 cvcbscr6 cvcbscr7 cvcbscr8 62 | 63 | t1_age t2_age t3_age t4_age t5_age 64 | t1_time t2_time t3_time t4_time t5_time 65 | t1_time2 t2_time2 t3_time2 t4_time2 t5_time2 66 | 67 | pn hhid hhidpn; 68 | 69 | MISSING are all (-9999) ; 70 | 71 | USEVAR are cdwrscr4 cdwrscr5 cdwrscr6 cdwrscr7 cdwrscr8 72 | dageyrs4 female; 73 | 74 | DEFINE: female=dsex-1; 75 | 76 | Output: SAMPSTAT PATTERNS; 77 | 78 | PLOT: 79 | Type is Plot2 Plot3; 80 | Series is cdwrscr4 cdwrscr5 cdwrscr6 cdwrscr7 cdwrscr8(*); 81 | 82 | -------------------------------------------------------------------------------- /Projects/HRS/Various/HRS_General Information.docx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Projects/HRS/Various/HRS_General Information.docx -------------------------------------------------------------------------------- /Projects/HRS/Various/HRS_General_VariableList.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Projects/HRS/Various/HRS_General_VariableList.xlsx -------------------------------------------------------------------------------- /Projects/HRS/Various/HRS_LGMGROWTH.inp: -------------------------------------------------------------------------------- 1 | Title: HRS_SEMGROWTH 2 | Data: 3 | File is HRS_WIDE_n2000.dat ; 4 | Variable: 5 | Names are 6 | secu idstrat idstudy idcohort 7 | wgtr4 wgtr5 wgtr6 wgtr7 wgtr8 wgtrbase wgt_pos 8 | 9 | ddobmth ddobyr dndimtch dndimth dndiyr ddodyrs ddthflg dfrstint 10 | dintmth4 dintmth5 dintmth6 dintmth7 dintmth8 11 | dsex dedudgr deduyrs 12 | dracehsp dracecnt dracewht draceblk draceoth 13 | 14 | dageyrs4 dageyrs5 dageyrs6 dageyrs7 dageyrs8 15 | dagecnt4 dagecnt5 dagecnt6 dagecnt7 dagecnt8 16 | dagesqr4 dagesqr5 dagesqr6 dagesqr7 dagesqr8 17 | dagec2_4 dagec2_5 dagec2_6 dagec2_7 dagec2_8 18 | 19 | dhhsize4 dhhsize5 dhhsize6 dhhsize7 dhhsize8 20 | dmarint4 dmarint5 dmarint6 dmarint7 dmarint8 21 | ewthfin4 ewthfin5 ewthfin6 ewthfin7 ewthfin8 22 | eincind4 einchh4 eincind5 einchh5 eincind6 einchh6 23 | eincind7 einchh7 eincind8 einchh8 24 | 25 | bexcfrq4 bexcfrq5 bexcfrq6 bexcfrq7 bexcfrq8 26 | bsmkevr4 bsmkevr5 bsmkevr6 bsmkevr7 bsmkevr8 27 | bsmknow4 bsmknow5 bsmknow6 bsmknow7 bsmknow8 28 | balcevr4 balcevr5 balcevr6 balcevr7 balcevr8 29 | balcdwk4 balcdwk5 balcdwk6 balcdwk7 balcdwk8 30 | balcddy4 balcddy5 balcddy6 balcddy7 balcddy8 31 | 32 | hvtlsts4 hvtlsts5 hvtlsts6 hvtlsts7 hvtlsts8 33 | hbmi4 hbmi5 hbmi6 hbmi7 hbmi8 34 | hsrhscr4 hsrhscr5 hsrhscr6 hsrhscr7 hsrhscr8 35 | hbrkhip4 hbrkhip5 hbrkhip6 hbrkhip7 hbrkhip8 36 | hbcksym4 hbcksym5 hbcksym6 hbcksym7 hbcksym8 37 | hhbpdia4 hhbpdia5 hhbpdia6 hhbpdia7 hhbpdia8 38 | hdibdia4 hdibdia5 hdibdia6 hdibdia7 hdibdia8 39 | hcandia4 hcandia5 hcandia6 hcandia7 hcandia8 40 | hlngdia4 hlngdia5 hlngdia6 hlngdia7 hlngdia8 41 | hpsydia4 hpsydia5 hpsydia6 hpsydia7 hpsydia8 42 | hartdia4 hartdia5 hartdia6 hartdia7 hartdia8 43 | hstkdia4 hstkdia5 hstkdia6 hstkdia7 hstkdia8 44 | hhrtdia4 hhrtdia5 hhrtdia6 hhrtdia7 hhrtdia8 45 | hiad3pt4 hiad3pt5 hiad3pt6 hiad3pt7 hiad3pt8 46 | hiad5pt4 hiad5pt5 hiad5pt6 hiad5pt7 hiad5pt8 47 | hadl3pt4 hadl3pt5 hadl3pt6 hadl3pt7 hadl3pt8 48 | hadl5pt4 hadl5pt5 hadl5pt6 hadl5pt7 hadl5pt8 49 | 50 | pcsdsum4 pcsdsum5 pcsdsum6 pcsdsum7 pcsdsum8 51 | csrmscr4 csrmscr5 csrmscr6 csrmscr7 csrmscr8 52 | cticlow4 cticlow5 cticlow6 cticlow7 cticlow8 53 | ctic9pt4 ctic9pt5 ctic9pt6 ctic9pt7 ctic9pt8 54 | ciwrstd4 ciwrstd5 ciwrstd6 ciwrstd7 ciwrstd8 55 | cdwrstd4 cdwrstd5 cdwrstd6 cdwrstd7 cdwrstd8 56 | ciwrscr4 ciwrscr5 ciwrscr6 ciwrscr7 ciwrscr8 57 | cdwrscr4 cdwrscr5 cdwrscr6 cdwrscr7 cdwrscr8 58 | cssstd4 cssstd5 cssstd6 cssstd7 cssstd8 59 | cssscr4 cssscr5 cssscr6 cssscr7 cssscr8 60 | cvcbstd4 cvcbstd5 cvcbstd6 cvcbstd7 cvcbstd8 61 | cvcbscr4 cvcbscr5 cvcbscr6 cvcbscr7 cvcbscr8 62 | 63 | t1age t2age t3age t4age t5age 64 | t1 t2 t3 t4 t5 65 | t1_time2 t2_time2 t3_time2 t4_time2 t5_time2 66 | 67 | pn hhid hhidpn; 68 | 69 | Missing are all (-9999) ; 70 | Missing are all (-999) ; 71 | 72 | USEVAR are t1 t2 t3 t4 t5 73 | CDWR1 CDWR2 CDWR3 CDWR4 CDWR5 ;! age65 female agefem; 74 | 75 | TSCORES = t1 t2 t3 t4 t5; 76 | 77 | Define: age65=dagecnt4; female=dsex-1; agefem=age65*female; 78 | CDWR1=cdwrscr4; CDWR2=cdwrscr5; CDWR3=cdwrscr6; CDWR4=cdwrscr7; CDWR5=cdwrscr8; 79 | 80 | Analysis: 81 | Type = RANDOM; 82 | 83 | Model: I S | cdwr1-cdwr5 AT t1-t5; 84 | 85 | CDWR1(2); 86 | CDWR2(2); 87 | CDWR3(2); 88 | CDWR4(2); 89 | CDWR5(2); 90 | 91 | PLOT: 92 | Type is Plot1 Plot2 Plot3; 93 | Series is CDWR1-CDWR5(*); 94 | 95 | 96 | -------------------------------------------------------------------------------- /Projects/HRS/Various/HRS_LGMGROWTH_ExampWriteup.docx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Projects/HRS/Various/HRS_LGMGROWTH_ExampWriteup.docx -------------------------------------------------------------------------------- /Projects/HRS/Various/HRS_LGMGROWTH_age.inp: -------------------------------------------------------------------------------- 1 | Title: HRS_SEMGROWTH 2 | Data: 3 | File is HRS_WIDE_n2000.dat ; 4 | Variable: 5 | Names are 6 | secu idstrat idstudy idcohort 7 | wgtr4 wgtr5 wgtr6 wgtr7 wgtr8 wgtrbase wgt_pos 8 | 9 | ddobmth ddobyr dndimtch dndimth dndiyr ddodyrs ddthflg dfrstint 10 | dintmth4 dintmth5 dintmth6 dintmth7 dintmth8 11 | dsex dedudgr deduyrs 12 | dracehsp dracecnt dracewht draceblk draceoth 13 | 14 | dageyrs4 dageyrs5 dageyrs6 dageyrs7 dageyrs8 15 | dagecnt4 dagecnt5 dagecnt6 dagecnt7 dagecnt8 16 | dagesqr4 dagesqr5 dagesqr6 dagesqr7 dagesqr8 17 | dagec2_4 dagec2_5 dagec2_6 dagec2_7 dagec2_8 18 | 19 | dhhsize4 dhhsize5 dhhsize6 dhhsize7 dhhsize8 20 | dmarint4 dmarint5 dmarint6 dmarint7 dmarint8 21 | ewthfin4 ewthfin5 ewthfin6 ewthfin7 ewthfin8 22 | eincind4 einchh4 eincind5 einchh5 eincind6 einchh6 23 | eincind7 einchh7 eincind8 einchh8 24 | 25 | bexcfrq4 bexcfrq5 bexcfrq6 bexcfrq7 bexcfrq8 26 | bsmkevr4 bsmkevr5 bsmkevr6 bsmkevr7 bsmkevr8 27 | bsmknow4 bsmknow5 bsmknow6 bsmknow7 bsmknow8 28 | balcevr4 balcevr5 balcevr6 balcevr7 balcevr8 29 | balcdwk4 balcdwk5 balcdwk6 balcdwk7 balcdwk8 30 | balcddy4 balcddy5 balcddy6 balcddy7 balcddy8 31 | 32 | hvtlsts4 hvtlsts5 hvtlsts6 hvtlsts7 hvtlsts8 33 | hbmi4 hbmi5 hbmi6 hbmi7 hbmi8 34 | hsrhscr4 hsrhscr5 hsrhscr6 hsrhscr7 hsrhscr8 35 | hbrkhip4 hbrkhip5 hbrkhip6 hbrkhip7 hbrkhip8 36 | hbcksym4 hbcksym5 hbcksym6 hbcksym7 hbcksym8 37 | hhbpdia4 hhbpdia5 hhbpdia6 hhbpdia7 hhbpdia8 38 | hdibdia4 hdibdia5 hdibdia6 hdibdia7 hdibdia8 39 | hcandia4 hcandia5 hcandia6 hcandia7 hcandia8 40 | hlngdia4 hlngdia5 hlngdia6 hlngdia7 hlngdia8 41 | hpsydia4 hpsydia5 hpsydia6 hpsydia7 hpsydia8 42 | hartdia4 hartdia5 hartdia6 hartdia7 hartdia8 43 | hstkdia4 hstkdia5 hstkdia6 hstkdia7 hstkdia8 44 | hhrtdia4 hhrtdia5 hhrtdia6 hhrtdia7 hhrtdia8 45 | hiad3pt4 hiad3pt5 hiad3pt6 hiad3pt7 hiad3pt8 46 | hiad5pt4 hiad5pt5 hiad5pt6 hiad5pt7 hiad5pt8 47 | hadl3pt4 hadl3pt5 hadl3pt6 hadl3pt7 hadl3pt8 48 | hadl5pt4 hadl5pt5 hadl5pt6 hadl5pt7 hadl5pt8 49 | 50 | pcsdsum4 pcsdsum5 pcsdsum6 pcsdsum7 pcsdsum8 51 | csrmscr4 csrmscr5 csrmscr6 csrmscr7 csrmscr8 52 | cticlow4 cticlow5 cticlow6 cticlow7 cticlow8 53 | ctic9pt4 ctic9pt5 ctic9pt6 ctic9pt7 ctic9pt8 54 | ciwrstd4 ciwrstd5 ciwrstd6 ciwrstd7 ciwrstd8 55 | cdwrstd4 cdwrstd5 cdwrstd6 cdwrstd7 cdwrstd8 56 | ciwrscr4 ciwrscr5 ciwrscr6 ciwrscr7 ciwrscr8 57 | cdwrscr4 cdwrscr5 cdwrscr6 cdwrscr7 cdwrscr8 58 | cssstd4 cssstd5 cssstd6 cssstd7 cssstd8 59 | cssscr4 cssscr5 cssscr6 cssscr7 cssscr8 60 | cvcbstd4 cvcbstd5 cvcbstd6 cvcbstd7 cvcbstd8 61 | cvcbscr4 cvcbscr5 cvcbscr6 cvcbscr7 cvcbscr8 62 | 63 | t1age t2age t3age t4age t5age 64 | t1 t2 t3 t4 t5 65 | t1_time2 t2_time2 t3_time2 t4_time2 t5_time2 66 | 67 | pn hhid hhidpn; 68 | 69 | Missing are all (-9999) ; 70 | 71 | USEVAR are dagecnt4 dagecnt5 dagecnt6 dagecnt7 dagecnt8 72 | CDWR1 CDWR2 CDWR3 CDWR4 CDWR5 age65; ! female agefem; 73 | 74 | TSCORES = dagecnt4 dagecnt5 dagecnt6 dagecnt7 dagecnt8 ; 75 | 76 | Define: age65=dagecnt4; female=dsex-1; agefem=age65*female; 77 | CDWR1=cdwrscr4; CDWR2=cdwrscr5; CDWR3=cdwrscr6; CDWR4=cdwrscr7; CDWR5=cdwrscr8; 78 | 79 | Analysis: 80 | Type = RANDOM; 81 | 82 | Model: I S | cdwr1-cdwr5 AT dagecnt4-dagecnt8 ; 83 | 84 | CDWR1(2); 85 | CDWR2(2); 86 | CDWR3(2); 87 | CDWR4(2); 88 | CDWR5(2); 89 | 90 | I ON age65; 91 | S ON age65; 92 | 93 | Output: 94 | 95 | -------------------------------------------------------------------------------- /Projects/HRS/Various/HRS_LGMGROWTH_piecewise.inp: -------------------------------------------------------------------------------- 1 | Title: HRS_SEMGROWTH 2 | Data: 3 | File is HRS_WIDE_n2000.dat ; 4 | Variable: 5 | Names are 6 | secu idstrat idstudy idcohort 7 | wgtr4 wgtr5 wgtr6 wgtr7 wgtr8 wgtrbase wgt_pos 8 | 9 | ddobmth ddobyr dndimtch dndimth dndiyr ddodyrs ddthflg dfrstint 10 | dintmth4 dintmth5 dintmth6 dintmth7 dintmth8 11 | dsex dedudgr deduyrs 12 | dracehsp dracecnt dracewht draceblk draceoth 13 | 14 | dageyrs4 dageyrs5 dageyrs6 dageyrs7 dageyrs8 15 | dagecnt4 dagecnt5 dagecnt6 dagecnt7 dagecnt8 16 | dagesqr4 dagesqr5 dagesqr6 dagesqr7 dagesqr8 17 | dagec2_4 dagec2_5 dagec2_6 dagec2_7 dagec2_8 18 | 19 | dhhsize4 dhhsize5 dhhsize6 dhhsize7 dhhsize8 20 | dmarint4 dmarint5 dmarint6 dmarint7 dmarint8 21 | ewthfin4 ewthfin5 ewthfin6 ewthfin7 ewthfin8 22 | eincind4 einchh4 eincind5 einchh5 eincind6 einchh6 23 | eincind7 einchh7 eincind8 einchh8 24 | 25 | bexcfrq4 bexcfrq5 bexcfrq6 bexcfrq7 bexcfrq8 26 | bsmkevr4 bsmkevr5 bsmkevr6 bsmkevr7 bsmkevr8 27 | bsmknow4 bsmknow5 bsmknow6 bsmknow7 bsmknow8 28 | balcevr4 balcevr5 balcevr6 balcevr7 balcevr8 29 | balcdwk4 balcdwk5 balcdwk6 balcdwk7 balcdwk8 30 | balcddy4 balcddy5 balcddy6 balcddy7 balcddy8 31 | 32 | hvtlsts4 hvtlsts5 hvtlsts6 hvtlsts7 hvtlsts8 33 | hbmi4 hbmi5 hbmi6 hbmi7 hbmi8 34 | hsrhscr4 hsrhscr5 hsrhscr6 hsrhscr7 hsrhscr8 35 | hbrkhip4 hbrkhip5 hbrkhip6 hbrkhip7 hbrkhip8 36 | hbcksym4 hbcksym5 hbcksym6 hbcksym7 hbcksym8 37 | hhbpdia4 hhbpdia5 hhbpdia6 hhbpdia7 hhbpdia8 38 | hdibdia4 hdibdia5 hdibdia6 hdibdia7 hdibdia8 39 | hcandia4 hcandia5 hcandia6 hcandia7 hcandia8 40 | hlngdia4 hlngdia5 hlngdia6 hlngdia7 hlngdia8 41 | hpsydia4 hpsydia5 hpsydia6 hpsydia7 hpsydia8 42 | hartdia4 hartdia5 hartdia6 hartdia7 hartdia8 43 | hstkdia4 hstkdia5 hstkdia6 hstkdia7 hstkdia8 44 | hhrtdia4 hhrtdia5 hhrtdia6 hhrtdia7 hhrtdia8 45 | hiad3pt4 hiad3pt5 hiad3pt6 hiad3pt7 hiad3pt8 46 | hiad5pt4 hiad5pt5 hiad5pt6 hiad5pt7 hiad5pt8 47 | hadl3pt4 hadl3pt5 hadl3pt6 hadl3pt7 hadl3pt8 48 | hadl5pt4 hadl5pt5 hadl5pt6 hadl5pt7 hadl5pt8 49 | 50 | pcsdsum4 pcsdsum5 pcsdsum6 pcsdsum7 pcsdsum8 51 | csrmscr4 csrmscr5 csrmscr6 csrmscr7 csrmscr8 52 | cticlow4 cticlow5 cticlow6 cticlow7 cticlow8 53 | ctic9pt4 ctic9pt5 ctic9pt6 ctic9pt7 ctic9pt8 54 | ciwrstd4 ciwrstd5 ciwrstd6 ciwrstd7 ciwrstd8 55 | cdwrstd4 cdwrstd5 cdwrstd6 cdwrstd7 cdwrstd8 56 | ciwrscr4 ciwrscr5 ciwrscr6 ciwrscr7 ciwrscr8 57 | cdwrscr4 cdwrscr5 cdwrscr6 cdwrscr7 cdwrscr8 58 | cssstd4 cssstd5 cssstd6 cssstd7 cssstd8 59 | cssscr4 cssscr5 cssscr6 cssscr7 cssscr8 60 | cvcbstd4 cvcbstd5 cvcbstd6 cvcbstd7 cvcbstd8 61 | cvcbscr4 cvcbscr5 cvcbscr6 cvcbscr7 cvcbscr8 62 | 63 | t1age t2age t3age t4age t5age 64 | t1 t2 t3 t4 t5 65 | t1_time2 t2_time2 t3_time2 t4_time2 t5_time2 66 | 67 | pn hhid hhidpn; 68 | 69 | Missing are all (-9999) ; 70 | 71 | USEVAR are CDWR1 CDWR2 CDWR3 CDWR4 CDWR5 age65; ! female agefem; 72 | 73 | Define: age65=dagecnt4; female=dsex-1; agefem=age65*female; 74 | CDWR1=cdwrscr4; CDWR2=cdwrscr5; CDWR3=cdwrscr6; CDWR4=cdwrscr7; CDWR5=cdwrscr8; 75 | 76 | Analysis: 77 | Type = RANDOM; 78 | 79 | Model: 80 | 81 | ! I S1 | cdwr1@0 cdwr2@2 cdwr3@2 cdwr4@2 cdwr5@2; !S1 and S2; 82 | ! I S2 | cdwr1@0 cdwr2@0 cdwr3@2 cdwr4@4 cdwr5@6; 83 | 84 | I S1 | cdwr1@0 cdwr2@2 cdwr3@4 cdwr4@6 cdwr5@8; !Slope & Deviation Slope; 85 | I S2 | cdwr1@0 cdwr2@0 cdwr3@2 cdwr4@4 cdwr5@6; 86 | 87 | CDWR1(2); 88 | CDWR2(2); 89 | CDWR3(2); 90 | CDWR4(2); 91 | CDWR5(2); 92 | 93 | I ON age65; 94 | S1 ON age65; 95 | S2 ON age65; 96 | 97 | Output: 98 | 99 | 100 | -------------------------------------------------------------------------------- /Projects/HRS/Various/HRS_LGMGROWTH_timestudy.inp: -------------------------------------------------------------------------------- 1 | Title: HRS_SEMGROWTH 2 | Data: 3 | File is HRS_WIDE_n2000.dat ; 4 | Variable: 5 | Names are 6 | secu idstrat idstudy idcohort 7 | wgtr4 wgtr5 wgtr6 wgtr7 wgtr8 wgtrbase wgt_pos 8 | 9 | ddobmth ddobyr dndimtch dndimth dndiyr ddodyrs ddthflg dfrstint 10 | dintmth4 dintmth5 dintmth6 dintmth7 dintmth8 11 | dsex dedudgr deduyrs 12 | dracehsp dracecnt dracewht draceblk draceoth 13 | 14 | dageyrs4 dageyrs5 dageyrs6 dageyrs7 dageyrs8 15 | dagecnt4 dagecnt5 dagecnt6 dagecnt7 dagecnt8 16 | dagesqr4 dagesqr5 dagesqr6 dagesqr7 dagesqr8 17 | dagec2_4 dagec2_5 dagec2_6 dagec2_7 dagec2_8 18 | 19 | dhhsize4 dhhsize5 dhhsize6 dhhsize7 dhhsize8 20 | dmarint4 dmarint5 dmarint6 dmarint7 dmarint8 21 | ewthfin4 ewthfin5 ewthfin6 ewthfin7 ewthfin8 22 | eincind4 einchh4 eincind5 einchh5 eincind6 einchh6 23 | eincind7 einchh7 eincind8 einchh8 24 | 25 | bexcfrq4 bexcfrq5 bexcfrq6 bexcfrq7 bexcfrq8 26 | bsmkevr4 bsmkevr5 bsmkevr6 bsmkevr7 bsmkevr8 27 | bsmknow4 bsmknow5 bsmknow6 bsmknow7 bsmknow8 28 | balcevr4 balcevr5 balcevr6 balcevr7 balcevr8 29 | balcdwk4 balcdwk5 balcdwk6 balcdwk7 balcdwk8 30 | balcddy4 balcddy5 balcddy6 balcddy7 balcddy8 31 | 32 | hvtlsts4 hvtlsts5 hvtlsts6 hvtlsts7 hvtlsts8 33 | hbmi4 hbmi5 hbmi6 hbmi7 hbmi8 34 | hsrhscr4 hsrhscr5 hsrhscr6 hsrhscr7 hsrhscr8 35 | hbrkhip4 hbrkhip5 hbrkhip6 hbrkhip7 hbrkhip8 36 | hbcksym4 hbcksym5 hbcksym6 hbcksym7 hbcksym8 37 | hhbpdia4 hhbpdia5 hhbpdia6 hhbpdia7 hhbpdia8 38 | hdibdia4 hdibdia5 hdibdia6 hdibdia7 hdibdia8 39 | hcandia4 hcandia5 hcandia6 hcandia7 hcandia8 40 | hlngdia4 hlngdia5 hlngdia6 hlngdia7 hlngdia8 41 | hpsydia4 hpsydia5 hpsydia6 hpsydia7 hpsydia8 42 | hartdia4 hartdia5 hartdia6 hartdia7 hartdia8 43 | hstkdia4 hstkdia5 hstkdia6 hstkdia7 hstkdia8 44 | hhrtdia4 hhrtdia5 hhrtdia6 hhrtdia7 hhrtdia8 45 | hiad3pt4 hiad3pt5 hiad3pt6 hiad3pt7 hiad3pt8 46 | hiad5pt4 hiad5pt5 hiad5pt6 hiad5pt7 hiad5pt8 47 | hadl3pt4 hadl3pt5 hadl3pt6 hadl3pt7 hadl3pt8 48 | hadl5pt4 hadl5pt5 hadl5pt6 hadl5pt7 hadl5pt8 49 | 50 | pcsdsum4 pcsdsum5 pcsdsum6 pcsdsum7 pcsdsum8 51 | csrmscr4 csrmscr5 csrmscr6 csrmscr7 csrmscr8 52 | cticlow4 cticlow5 cticlow6 cticlow7 cticlow8 53 | ctic9pt4 ctic9pt5 ctic9pt6 ctic9pt7 ctic9pt8 54 | ciwrstd4 ciwrstd5 ciwrstd6 ciwrstd7 ciwrstd8 55 | cdwrstd4 cdwrstd5 cdwrstd6 cdwrstd7 cdwrstd8 56 | ciwrscr4 ciwrscr5 ciwrscr6 ciwrscr7 ciwrscr8 57 | cdwrscr4 cdwrscr5 cdwrscr6 cdwrscr7 cdwrscr8 58 | cssstd4 cssstd5 cssstd6 cssstd7 cssstd8 59 | cssscr4 cssscr5 cssscr6 cssscr7 cssscr8 60 | cvcbstd4 cvcbstd5 cvcbstd6 cvcbstd7 cvcbstd8 61 | cvcbscr4 cvcbscr5 cvcbscr6 cvcbscr7 cvcbscr8 62 | 63 | t1age t2age t3age t4age t5age 64 | t1 t2 t3 t4 t5 65 | t1_time2 t2_time2 t3_time2 t4_time2 t5_time2 66 | 67 | pn hhid hhidpn; 68 | 69 | Missing are all (-9999) ; 70 | 71 | USEVAR are t1 t2 t3 t4 t5 72 | CDWR1 CDWR2 CDWR3 CDWR4 CDWR5 age65; ! female agefem; 73 | 74 | TSCORES = t1 t2 t3 t4 t5; 75 | 76 | Define: age65=dagecnt4; female=dsex-1; agefem=age65*female; 77 | CDWR1=cdwrscr4; CDWR2=cdwrscr5; CDWR3=cdwrscr6; CDWR4=cdwrscr7; CDWR5=cdwrscr8; 78 | 79 | Analysis: 80 | Type = RANDOM; 81 | 82 | Model: I S | cdwr1-cdwr5 AT t1-t5; 83 | 84 | CDWR1(2); 85 | CDWR2(2); 86 | CDWR3(2); 87 | CDWR4(2); 88 | CDWR5(2); 89 | 90 | I ON age65; 91 | S ON age65; 92 | 93 | Output: 94 | 95 | 96 | -------------------------------------------------------------------------------- /Projects/HRS/Various/dsHRS.R: -------------------------------------------------------------------------------- 1 | # remove all elements for a clean start 2 | rm(list=ls(all=TRUE)) 3 | cat("\014") 4 | 5 | 6 | ## @knitr InstallPackage 7 | # source("./Scripts/Utility/InstallPackages.R") 8 | 9 | 10 | 11 | ## @knitr LoadPackages 12 | require(sas7bdat) # for inputting data 13 | library(dplyr) # for general data manipulation 14 | # library(reshape2) # for data : wide <-> long 15 | # library(psych) # data summary + etc 16 | library(ggplot2) # graphing 17 | # library(nlme) # estimate fixed models | esp. gls() 18 | # library(lme4) # estimate mixed models | esp. lmer() 19 | # library(arm) # process model objects 20 | 21 | 22 | ## @knitr LoadData 23 | ds0 <- read.csv("~/GitHub/psy564/Data/Raw/HRS/HRS_WIDE_n2000.dat", header=F) 24 | dim(ds0) 25 | 26 | # namesare <- read.table("./Projects/HRS/HRS/namesare.txt", sep=" ") 27 | namesarePath <- "./Projects/HRS/Various/namesare.txt" 28 | namesare <- scan (namesarePath, what="character", sep=" ") 29 | names(ds0) <- namesare 30 | 31 | selectVars <- c() -------------------------------------------------------------------------------- /Projects/HRS/Various/hrs_basic.dgm: -------------------------------------------------------------------------------- 1 | VERSION 1.1.0 2 | INPUT 3 | TITLE: 4 | HRS_WIDE_BASIC; 5 | DATA: 6 | File is HRS_WIDE_n2000.dat ; 7 | VARIABLE: 8 | Names are 9 | secu idstrat idstudy idcohort 10 | wgtr4 wgtr5 wgtr6 wgtr7 wgtr8 wgtrbase wgt_pos 11 | ddobmth ddobyr dndimtch dndimth dndiyr ddodyrs ddthflg dfrstint 12 | dintmth4 dintmth5 dintmth6 dintmth7 dintmth8 13 | dsex dedudgr deduyrs 14 | dracehsp dracecnt dracewht draceblk draceoth 15 | dageyrs4 dageyrs5 dageyrs6 dageyrs7 dageyrs8 16 | dagecnt4 dagecnt5 dagecnt6 dagecnt7 dagecnt8 17 | dagesqr4 dagesqr5 dagesqr6 dagesqr7 dagesqr8 18 | dagec2_4 dagec2_5 dagec2_6 dagec2_7 dagec2_8 19 | dhhsize4 dhhsize5 dhhsize6 dhhsize7 dhhsize8 20 | dmarint4 dmarint5 dmarint6 dmarint7 dmarint8 21 | ewthfin4 ewthfin5 ewthfin6 ewthfin7 ewthfin8 22 | eincind4 einchh4 eincind5 einchh5 eincind6 einchh6 23 | eincind7 einchh7 eincind8 einchh8 24 | bexcfrq4 bexcfrq5 bexcfrq6 bexcfrq7 bexcfrq8 25 | bsmkevr4 bsmkevr5 bsmkevr6 bsmkevr7 bsmkevr8 26 | bsmknow4 bsmknow5 bsmknow6 bsmknow7 bsmknow8 27 | balcevr4 balcevr5 balcevr6 balcevr7 balcevr8 28 | balcdwk4 balcdwk5 balcdwk6 balcdwk7 balcdwk8 29 | balcddy4 balcddy5 balcddy6 balcddy7 balcddy8 30 | hvtlsts4 hvtlsts5 hvtlsts6 hvtlsts7 hvtlsts8 31 | hbmi4 hbmi5 hbmi6 hbmi7 hbmi8 32 | hsrhscr4 hsrhscr5 hsrhscr6 hsrhscr7 hsrhscr8 33 | hbrkhip4 hbrkhip5 hbrkhip6 hbrkhip7 hbrkhip8 34 | hbcksym4 hbcksym5 hbcksym6 hbcksym7 hbcksym8 35 | hhbpdia4 hhbpdia5 hhbpdia6 hhbpdia7 hhbpdia8 36 | hdibdia4 hdibdia5 hdibdia6 hdibdia7 hdibdia8 37 | hcandia4 hcandia5 hcandia6 hcandia7 hcandia8 38 | hlngdia4 hlngdia5 hlngdia6 hlngdia7 hlngdia8 39 | hpsydia4 hpsydia5 hpsydia6 hpsydia7 hpsydia8 40 | hartdia4 hartdia5 hartdia6 hartdia7 hartdia8 41 | hstkdia4 hstkdia5 hstkdia6 hstkdia7 hstkdia8 42 | hhrtdia4 hhrtdia5 hhrtdia6 hhrtdia7 hhrtdia8 43 | hiad3pt4 hiad3pt5 hiad3pt6 hiad3pt7 hiad3pt8 44 | hiad5pt4 hiad5pt5 hiad5pt6 hiad5pt7 hiad5pt8 45 | hadl3pt4 hadl3pt5 hadl3pt6 hadl3pt7 hadl3pt8 46 | hadl5pt4 hadl5pt5 hadl5pt6 hadl5pt7 hadl5pt8 47 | pcsdsum4 pcsdsum5 pcsdsum6 pcsdsum7 pcsdsum8 48 | csrmscr4 csrmscr5 csrmscr6 csrmscr7 csrmscr8 49 | cticlow4 cticlow5 cticlow6 cticlow7 cticlow8 50 | ctic9pt4 ctic9pt5 ctic9pt6 ctic9pt7 ctic9pt8 51 | ciwrstd4 ciwrstd5 ciwrstd6 ciwrstd7 ciwrstd8 52 | cdwrstd4 cdwrstd5 cdwrstd6 cdwrstd7 cdwrstd8 53 | ciwrscr4 ciwrscr5 ciwrscr6 ciwrscr7 ciwrscr8 54 | cdwrscr4 cdwrscr5 cdwrscr6 cdwrscr7 cdwrscr8 55 | cssstd4 cssstd5 cssstd6 cssstd7 cssstd8 56 | cssscr4 cssscr5 cssscr6 cssscr7 cssscr8 57 | cvcbstd4 cvcbstd5 cvcbstd6 cvcbstd7 cvcbstd8 58 | cvcbscr4 cvcbscr5 cvcbscr6 cvcbscr7 cvcbscr8 59 | t1_age t2_age t3_age t4_age t5_age 60 | t1_time t2_time t3_time t4_time t5_time 61 | t1_time2 t2_time2 t3_time2 t4_time2 t5_time2 62 | pn hhid hhidpn; 63 | MISSING are all (-9999) ; 64 | USEVAR are cdwrscr4 cdwrscr5 cdwrscr6 cdwrscr7 cdwrscr8 65 | dageyrs4 female; 66 | DEFINE: 67 | female=dsex-1; 68 | OUTPUT: 69 | SAMPSTAT PATTERNS; 70 | PLOT: 71 | Type is Plot2 Plot3; 72 | Series is cdwrscr4 cdwrscr5 cdwrscr6 cdwrscr7 cdwrscr8(*); 73 | INPUT_END 74 | 2 75 | 0 76 | 0 77 | 0 78 | ML 79 | 1 80 | GENERAL 81 | 0 82 | 7 83 | 0 84 | 0 85 | cdwrscr4 cdwrscr5 cdwrscr6 cdwrscr7 cdwrscr8 dageyrs4 female 86 | 1 87 | 0 0 0 0 0 0 0 88 | 0 89 | 0 90 | 5 1 cdwrscr4 5.060 0.200 91 | 5 1 cdwrscr5 4.526 0.189 92 | 5 1 cdwrscr6 4.784 0.211 93 | 5 1 cdwrscr7 3.912 0.162 94 | 5 1 cdwrscr8 4.320 0.185 95 | 5 1 dageyrs4 122.295 4.599 96 | 5 1 female 0.247 0.008 97 | -------------------------------------------------------------------------------- /Projects/HRS/Various/hrs_basic.gh5: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Projects/HRS/Various/hrs_basic.gh5 -------------------------------------------------------------------------------- /Projects/HRS/Various/hrs_lgmgrowth.dgm: -------------------------------------------------------------------------------- 1 | VERSION 1.1.0 2 | INPUT 3 | TITLE: 4 | HRS_SEMGROWTH 5 | DATA: 6 | File is HRS_WIDE_n2000.dat ; 7 | VARIABLE: 8 | Names are 9 | secu idstrat idstudy idcohort 10 | wgtr4 wgtr5 wgtr6 wgtr7 wgtr8 wgtrbase wgt_pos 11 | ddobmth ddobyr dndimtch dndimth dndiyr ddodyrs ddthflg dfrstint 12 | dintmth4 dintmth5 dintmth6 dintmth7 dintmth8 13 | dsex dedudgr deduyrs 14 | dracehsp dracecnt dracewht draceblk draceoth 15 | dageyrs4 dageyrs5 dageyrs6 dageyrs7 dageyrs8 16 | dagecnt4 dagecnt5 dagecnt6 dagecnt7 dagecnt8 17 | dagesqr4 dagesqr5 dagesqr6 dagesqr7 dagesqr8 18 | dagec2_4 dagec2_5 dagec2_6 dagec2_7 dagec2_8 19 | dhhsize4 dhhsize5 dhhsize6 dhhsize7 dhhsize8 20 | dmarint4 dmarint5 dmarint6 dmarint7 dmarint8 21 | ewthfin4 ewthfin5 ewthfin6 ewthfin7 ewthfin8 22 | eincind4 einchh4 eincind5 einchh5 eincind6 einchh6 23 | eincind7 einchh7 eincind8 einchh8 24 | bexcfrq4 bexcfrq5 bexcfrq6 bexcfrq7 bexcfrq8 25 | bsmkevr4 bsmkevr5 bsmkevr6 bsmkevr7 bsmkevr8 26 | bsmknow4 bsmknow5 bsmknow6 bsmknow7 bsmknow8 27 | balcevr4 balcevr5 balcevr6 balcevr7 balcevr8 28 | balcdwk4 balcdwk5 balcdwk6 balcdwk7 balcdwk8 29 | balcddy4 balcddy5 balcddy6 balcddy7 balcddy8 30 | hvtlsts4 hvtlsts5 hvtlsts6 hvtlsts7 hvtlsts8 31 | hbmi4 hbmi5 hbmi6 hbmi7 hbmi8 32 | hsrhscr4 hsrhscr5 hsrhscr6 hsrhscr7 hsrhscr8 33 | hbrkhip4 hbrkhip5 hbrkhip6 hbrkhip7 hbrkhip8 34 | hbcksym4 hbcksym5 hbcksym6 hbcksym7 hbcksym8 35 | hhbpdia4 hhbpdia5 hhbpdia6 hhbpdia7 hhbpdia8 36 | hdibdia4 hdibdia5 hdibdia6 hdibdia7 hdibdia8 37 | hcandia4 hcandia5 hcandia6 hcandia7 hcandia8 38 | hlngdia4 hlngdia5 hlngdia6 hlngdia7 hlngdia8 39 | hpsydia4 hpsydia5 hpsydia6 hpsydia7 hpsydia8 40 | hartdia4 hartdia5 hartdia6 hartdia7 hartdia8 41 | hstkdia4 hstkdia5 hstkdia6 hstkdia7 hstkdia8 42 | hhrtdia4 hhrtdia5 hhrtdia6 hhrtdia7 hhrtdia8 43 | hiad3pt4 hiad3pt5 hiad3pt6 hiad3pt7 hiad3pt8 44 | hiad5pt4 hiad5pt5 hiad5pt6 hiad5pt7 hiad5pt8 45 | hadl3pt4 hadl3pt5 hadl3pt6 hadl3pt7 hadl3pt8 46 | hadl5pt4 hadl5pt5 hadl5pt6 hadl5pt7 hadl5pt8 47 | pcsdsum4 pcsdsum5 pcsdsum6 pcsdsum7 pcsdsum8 48 | csrmscr4 csrmscr5 csrmscr6 csrmscr7 csrmscr8 49 | cticlow4 cticlow5 cticlow6 cticlow7 cticlow8 50 | ctic9pt4 ctic9pt5 ctic9pt6 ctic9pt7 ctic9pt8 51 | ciwrstd4 ciwrstd5 ciwrstd6 ciwrstd7 ciwrstd8 52 | cdwrstd4 cdwrstd5 cdwrstd6 cdwrstd7 cdwrstd8 53 | ciwrscr4 ciwrscr5 ciwrscr6 ciwrscr7 ciwrscr8 54 | cdwrscr4 cdwrscr5 cdwrscr6 cdwrscr7 cdwrscr8 55 | cssstd4 cssstd5 cssstd6 cssstd7 cssstd8 56 | cssscr4 cssscr5 cssscr6 cssscr7 cssscr8 57 | cvcbstd4 cvcbstd5 cvcbstd6 cvcbstd7 cvcbstd8 58 | cvcbscr4 cvcbscr5 cvcbscr6 cvcbscr7 cvcbscr8 59 | t1age t2age t3age t4age t5age 60 | t1 t2 t3 t4 t5 61 | t1_time2 t2_time2 t3_time2 t4_time2 t5_time2 62 | pn hhid hhidpn; 63 | Missing are all (-9999) ; 64 | Missing are all (-999) ; 65 | USEVAR are t1 t2 t3 t4 t5 66 | CDWR1 CDWR2 CDWR3 CDWR4 CDWR5 ; 67 | TSCORES = t1 t2 t3 t4 t5; 68 | DEFINE: 69 | age65=dagecnt4; female=dsex-1; agefem=age65*female; 70 | CDWR1=cdwrscr4; CDWR2=cdwrscr5; CDWR3=cdwrscr6; CDWR4=cdwrscr7; CDWR5=cdwrscr8; 71 | ANALYSIS: 72 | Type = RANDOM; 73 | PLOT: 74 | Type is Plot1 Plot2 Plot3; 75 | Series is CDWR1-CDWR5(*); 76 | MODEL: 77 | I S | cdwr1-cdwr5 AT t1-t5; 78 | CDWR1(2); 79 | CDWR2(2); 80 | CDWR3(2); 81 | CDWR4(2); 82 | CDWR5(2); 83 | INPUT_END 84 | 2 85 | 0 86 | 0 87 | 0 88 | MLR 89 | 1 90 | GENERAL 91 | 0 92 | 5 93 | 2 94 | 0 95 | cdwr1 cdwr2 cdwr3 cdwr4 cdwr5 i s 96 | 2 97 | 1 1 1 1 1 0 0 98 | 0 99 | 0 100 | 6 1 i cdwr1 1 101 | 6 1 s cdwr1 t1 102 | 6 1 i cdwr2 1 103 | 6 1 s cdwr2 t2 104 | 6 1 i cdwr3 1 105 | 6 1 s cdwr3 t3 106 | 6 1 i cdwr4 1 107 | 6 1 s cdwr4 t4 108 | 6 1 i cdwr5 1 109 | 6 1 s cdwr5 t5 110 | 2 1 s i -0.048 0.021 111 | 4 1 cdwr1 2.126 0.084 112 | 4 1 cdwr2 2.126 0.084 113 | 4 1 cdwr3 2.126 0.084 114 | 4 1 cdwr4 2.126 0.084 115 | 4 1 cdwr5 2.126 0.084 116 | 5 1 i 2.733 0.170 117 | 5 1 s 0.012 0.004 118 | -------------------------------------------------------------------------------- /Projects/HRS/Various/hrs_lgmgrowth.gh5: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Projects/HRS/Various/hrs_lgmgrowth.gh5 -------------------------------------------------------------------------------- /Projects/HRS/Various/namesare.txt: -------------------------------------------------------------------------------- 1 | secu idstrat idstudy idcohort wgtr4 wgtr5 wgtr6 wgtr7 wgtr8 wgtrbase wgt_pos ddobmth ddobyr dndimtch dndimth dndiyr ddodyrs ddthflg dfrstint dintmth4 dintmth5 dintmth6 dintmth7 dintmth8 dsex dedudgr deduyrs dracehsp dracecnt dracewht draceblk draceoth dageyrs4 dageyrs5 dageyrs6 dageyrs7 dageyrs8 dagecnt4 dagecnt5 dagecnt6 dagecnt7 dagecnt8 dagesqr4 dagesqr5 dagesqr6 dagesqr7 dagesqr8 dagec2_4 dagec2_5 dagec2_6 dagec2_7 dagec2_8 dhhsize4 dhhsize5 dhhsize6 dhhsize7 dhhsize8 dmarint4 dmarint5 dmarint6 dmarint7 dmarint8 ewthfin4 ewthfin5 ewthfin6 ewthfin7 ewthfin8 eincind4 einchh4 eincind5 einchh5 eincind6 einchh6 eincind7 einchh7 eincind8 einchh8 bexcfrq4 bexcfrq5 bexcfrq6 bexcfrq7 bexcfrq8 bsmkevr4 bsmkevr5 bsmkevr6 bsmkevr7 bsmkevr8 bsmknow4 bsmknow5 smknow6 bsmknow7 bsmknow8 balcevr4 balcevr5 balcevr6 balcevr7 balcevr8 balcdwk4 balcdwk5 balcdwk6 balcdwk7 balcdwk8 balcddy4 balcddy5 balcddy6 balcddy7 balcddy8 hvtlsts4 hvtlsts5 hvtlsts6 hvtlsts7 hvtlsts8 hbmi4 hbmi5 hbmi6 hbmi7 hbmi8 hsrhscr4 hsrhscr5 hsrhscr6 hsrhscr7 hsrhscr8 hbrkhip4 hbrkhip5 hbrkhip6 hbrkhip7 hbrkhip8 hbcksym4 hbcksym5 hbcksym6 hbcksym7 hbcksym8 hhbpdia4 hhbpdia5 hhbpdia6 hhbpdia7 hhbpdia8 hdibdia4 hdibdia5 hdibdia6 hdibdia7 hdibdia8 hcandia4 hcandia5 hcandia6 hcandia7 hcandia8 hlngdia4 hlngdia5 hlngdia6 hlngdia7 hlngdia8 hpsydia4 hpsydia5 hpsydia6 hpsydia7 hpsydia8 hartdia4 hartdia5 hartdia6 hartdia7 hartdia8 hstkdia4 hstkdia5 hstkdia6 hstkdia7 hstkdia8 hhrtdia4 hhrtdia5 hhrtdia6 hhrtdia7 hhrtdia8 hiad3pt4 hiad3pt5 hiad3pt6 hiad3pt7 hiad3pt8 hiad5pt4 hiad5pt5 hiad5pt6 hiad5pt7 hiad5pt8 hadl3pt4 hadl3pt5 hadl3pt6 hadl3pt7 hadl3pt8 hadl5pt4 hadl5pt5 hadl5pt6 hadl5pt7 hadl5pt8 pcsdsum4 pcsdsum5 pcsdsum6 pcsdsum7 pcsdsum8 csrmscr4 csrmscr5 csrmscr6 csrmscr7 csrmscr8 cticlow4 cticlow5 cticlow6 cticlow7 cticlow8 ctic9pt4 ctic9pt5 ctic9pt6 ctic9pt7 ctic9pt8 ciwrstd4 ciwrstd5 ciwrstd6 ciwrstd7 ciwrstd8 cdwrstd4 cdwrstd5 cdwrstd6 cdwrstd7 cdwrstd8 ciwrscr4 ciwrscr5 ciwrscr6 ciwrscr7 ciwrscr8 cdwrscr4 cdwrscr5 cdwrscr6 cdwrscr7 cdwrscr8 cssstd4 cssstd5 cssstd6 cssstd7 cssstd8 cssscr4 cssscr5 cssscr6 cssscr7 cssscr8 cvcbstd4 cvcbstd5 cvcbstd6 cvcbstd7 cvcbstd8 cvcbscr4 cvcbscr5 cvcbscr6 cvcbscr7 cvcbscr8 t1_age t2_age t3_age t4_age t5_age t1_time t2_time t3_time t4_time t5_time t1_time2 t2_time2 t3_time2 t4_time2 t5_time2 pn hhid hhidpn -------------------------------------------------------------------------------- /Projects/LMG_Mplus_primer.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/andkov/psy564/204e0a747ad2c05642a591844b45397df4e8c946/Projects/LMG_Mplus_primer.pdf -------------------------------------------------------------------------------- /Projects/README.md: -------------------------------------------------------------------------------- 1 | Integrating Mplus and R 2 | ---- 3 | 4 | ## Plotting using GH5 files 5 | 6 | The official jumping board into plotting GH5 is at [www.statmodel.com/mplus-R](http://www.statmodel.com/mplus-R/) 7 | 8 | Plots can be created in R using the GH5 files generated by Mplus and containing plot information. See [description of GH5 files](http://statmodel2.com/mplus-R/GH5_R.shtml). 9 | 10 | Functions that extract the needed information are stored in a separate script [mplus.R](http://www.statmodel.com/mplus-R/mplus.R) 11 | 12 | [Tutorial on how to work with mplus.R](http://www.statmodel.com/mplus-R/Mplus%20R%20tutorial.pdf) created by Muthen & Muthen. 13 | 14 | The R package that works with HDF5 (data format in which GH5 are stored) is [rhdf5](http://www.bioconductor.org/packages/release/bioc/vignettes/rhdf5/inst/doc/rhdf5.pdf) -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | Longitudinal Modeling 2 | ============ 3 | Scripts and libraries to accompany a graduate course on longitudinal modeling (PSY-564) taught at the University of Victoria in the spring of 2015 by Scott Hofer and Andriy Koval. 4 | -------------------------------------------------------------------------------- /Scripts/Data/LabelingFactorLevels.R: -------------------------------------------------------------------------------- 1 | # The following script declares the factor labels to be used with **dsL** 2 | # 3 | ########################################################################### 4 | 5 | #### SCALES #### 6 | 7 | ## sex ################################################################### 8 | sexLevels<- c(1,2,0) 9 | sexLabels<- c("Male","Female","No Information") 10 | 11 | varlist<-c("sex") 12 | for(i in varlist){ 13 | dsF[,paste0(i,"F")]<-ordered(dsF[,i], 14 | levels = sexLevels, 15 | labels = sexLabels) 16 | } 17 | ## race ################################################################## 18 | raceLevels<- c(1,2,3,4) 19 | raceLabels<- c("Black","Hispanic","Mixed (Non-H)","Non-B/Non-H") 20 | 21 | varlist<-c("race") 22 | for(i in varlist){ 23 | dsF[,paste0(i,"F")]<-ordered(dsF[,i], 24 | levels = raceLevels, 25 | labels = raceLabels) 26 | } 27 | ## birth month ########################################################### 28 | bmonthLevels<- c(1:12) 29 | bmonthLabels<- c("Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec") 30 | 31 | varlist<-c("bmonth") 32 | for(i in varlist){ 33 | dsF[,paste0(i,"F")]<-ordered(dsF[,i], 34 | levels = bmonthLevels, 35 | labels = bmonthLabels) 36 | } 37 | 38 | ## church attendance ##################################################### 39 | attendLevels<- c(1:8) 40 | attendLabelsShort<-c("Never", 41 | "Once or Twice", 42 | "< once/month", 43 | "~ once/month", 44 | "~ twice/month", 45 | "~ once/week", 46 | "Several times/week", 47 | "Everyday") 48 | attendLabels<-c( "Never", 49 | "Once or Twice", 50 | "Less than once/month", 51 | "About once/month", 52 | "About twice/month", 53 | "About once/week", 54 | "Several times/week", 55 | "Everyday") 56 | varlist<- c("attend") 57 | for(i in varlist){ 58 | dsF[,paste0(i,"F")]<-ordered(dsF[,i], 59 | levels = attendLevels, 60 | labels = attendLabels) 61 | } 62 | # The color scale developed for this variable 63 | attcol8<-c("Never"="#4575b4", 64 | "Once or Twice"="#74add1", 65 | "Less than once/month"="#abd9e9", 66 | "About once/month"="#e0f3f8", 67 | "About twice/month"="#fee090", 68 | "About once/week"="#fdae61", 69 | "Several times/week"="#f46d43", 70 | "Everyday"="#d73027") 71 | 72 | 73 | # ADD MORE VARIABLES HERE 74 | 75 | # Now data set contains a set of ghost Factor variables that can be used in graphing and modeling -------------------------------------------------------------------------------- /Scripts/Data/dsL.R: -------------------------------------------------------------------------------- 1 | # remove all elements for a clean start 2 | rm(list=ls(all=TRUE)) 3 | 4 | ## @knitr LoadPackages 5 | require(sas7bdat) 6 | require(Hmisc) 7 | 8 | ## @knitr LoadData 9 | pathDir <- getwd() 10 | pathFileSAS <- file.path(pathDir,"Chapters/02/SAS_Chapter2/SAS_Chapter2.sas7bdat") 11 | pathFileSPSS <- file.path(pathDir,"Chapters/02/SPSS_Chapter2/SPSS_Chapter2.sav") 12 | 13 | path_ds0 <- file.path(pathDir, "Data/Derived/02/ds0.Rds") 14 | path_dsL <- file.path(pathDir, "Data/Derived/02/dsL.Rds") 15 | 16 | 17 | ds0SAS <- read.sas7bdat(pathFileSAS, debug=TRUE) # Use this when running for the first time 18 | ds0SPSS <- Hmisc::spss.get(pathFileSPSS, use.value.labels = TRUE) 19 | 20 | saveRDS(object=ds0, file=path_ds0, compress="xz") # Use this when running for the first time 21 | ### Either use ds0 definition above or below. 22 | ds0<-readRDS(path_ds0) # This saves time # Use for subsequent run 23 | -------------------------------------------------------------------------------- /Scripts/Data/loadChapterDatasets.R: -------------------------------------------------------------------------------- 1 | # remove all elements for a clean start 2 | rm(list=ls(all=TRUE)) 3 | 4 | ## @knitr LoadPackages 5 | require(sas7bdat) 6 | 7 | ## @knitr LoadData 8 | pathDir <- getwd() 9 | pathCh2 <- file.path(pathDir,"Chapters/02/SAS_Chapter2/SAS_Chapter2.sas7bdat") 10 | pathCh3a <- file.path(pathDir,"Chapters/03/SAS_Chapter3a/SAS_Chapter3a.sas7bdat") 11 | pathCh3b <- file.path(pathDir,"Chapters/03/SAS_Chapter3b/SAS_Chapter3b.sas7bdat") 12 | pathCh4 <- file.path(pathDir,"Chapters/04/SAS_Chapter4/SAS_Chapter4.sas7bdat") 13 | pathCh5 <- file.path(pathDir,"Chapters/05/SAS_Chapter4/SAS_Chapter5.sas7bdat") 14 | pathCh6 <- file.path(pathDir,"Chapters/06/SAS_Chapter6/SAS_Chapter6.sas7bdat") 15 | pathCh7a <- file.path(pathDir,"Chapters/07/SAS_Chapter7a/SAS_Chapter7a.sas7bdat") 16 | pathCh7b <- file.path(pathDir,"Chapters/07/SAS_Chapter7b/SAS_Chapter7b.sas7bdat") 17 | pathCh8 <- file.path(pathDir,"Chapters/08/SAS_Chapter8/SAS_Chapter8.sas7bdat") 18 | pathCh9 <- file.path(pathDir,"Chapters/09/SAS_Chapter9/SAS_Chapter9.sas7bdat") 19 | pathCh10a <- file.path(pathDir,"Chapters/10/SAS_Chapter10a/SAS_Chapter10a.sas7bdat") 20 | pathCh10b <- file.path(pathDir,"Chapters/10/SAS_Chapter10b/SAS_Chapter10b.sas7bdat") 21 | pathCh11a <- file.path(pathDir,"Chapters/11/SAS_Chapter11a/SAS_Chapter11a.sas7bdat") 22 | pathCh11b <- file.path(pathDir,"Chapters/11/SAS_Chapter11b/SAS_Chapter11b.sas7bdat") 23 | pathCh12 <- file.path(pathDir,"Chapters/12/SAS_Chapter12/SAS_Chapter12.sas7bdat") 24 | 25 | 26 | 27 | dsL2 <- read.sas7bdat(pathCh2, debug=TRUE) 28 | dsL3a <- read.sas7bdat(pathCh3a, debug=TRUE) 29 | dsL3b <- read.sas7bdat(pathCh3b, debug=TRUE) 30 | dsL4 <- read.sas7bdat(pathCh4, debug=TRUE) 31 | dsL5 <- read.sas7bdat(pathCh5, debug=TRUE) 32 | dsL6 <- read.sas7bdat(pathCh6, debug=TRUE) 33 | dsL7a <- read.sas7bdat(pathCh7a, debug=TRUE) 34 | dsL7b <- read.sas7bdat(pathCh7b, debug=TRUE) 35 | dsL8 <- read.sas7bdat(pathCh8, debug=TRUE) 36 | dsL9 <- read.sas7bdat(pathCh9, debug=TRUE) 37 | dsL10a <- read.sas7bdat(pathCh10a, debug=TRUE) 38 | dsL10b <- read.sas7bdat(pathCh10b, debug=TRUE) 39 | dsL11a <- read.sas7bdat(pathCh11a, debug=TRUE) 40 | dsL11b <- read.sas7bdat(pathCh11b, debug=TRUE) 41 | dsL12 <- read.sas7bdat(pathCh12, debug=TRUE) 42 | 43 | # # path_dsL2 <- file.path(pathDir, "Data/Derived/02/dsL.Rds") 44 | # saveRDS(object=ds0, file=path_ds0, compress="xz") # Use this when running for the first time 45 | # ### Either use ds0 definition above or below. 46 | # ds0<-readRDS(path_ds0) # This saves time # Use for subsequent run 47 | 48 | 49 | write.csv(dsL6, file="Data/Derived/MPLUS_Chpater6.csv") 50 | -------------------------------------------------------------------------------- /Scripts/Graphs/AesDefine.R: -------------------------------------------------------------------------------- 1 | # Definitions of of aesthetics used in reports 2 | 3 | 4 | # COLORS 5 | ## the colors for response categories of item "attend" 6 | attendCol8<-c("Never"="#4575b4", 7 | "Once or Twice"="#74add1", 8 | "Less than once/month"="#abd9e9", 9 | "About once/month"="#e0f3f8", 10 | "About twice/month"="#fee090", 11 | "About once/week"="#fdae61", 12 | "Several times/week"="#f46d43", 13 | "Everyday"="#d73027") 14 | 15 | ## The color of cohorts 16 | byearCol5<- c("1980"="#9ecae1", 17 | "1981"="#6baed6", 18 | "1982"="#4292c6", 19 | "1983"="#2171b5", 20 | "1984"="#084594") 21 | 22 | 23 | ## the color of missing values 24 | NACol<- "#f9f9f9" #"#636363" 25 | 26 | 27 | # SIZES 28 | # guides and legends, but not axes and title 29 | baseSize<- 12 30 | 31 | 32 | # SHAPES 33 | 34 | # GROUPS 35 | 36 | # Variables that DO NOT change with time, TI - time invariant 37 | TIvars<-c("sample", "id", "sex","race", "bmonth","byear", 'attendPR', "relprefPR", "relraisedPR") 38 | 39 | # Variables that DO change with time, TV - time variant 40 | TVvars<- c("agemon", "ageyear", "famrel", "attend", 41 | "values","todo", "obeyed","pray", "decisions", 42 | "relpref", "bornagain", "faith", 43 | "calm", "blue", "happy", "depressed","nervous", 44 | "tv", "computer", "internet") 45 | 46 | # Service 47 | counterAge<- c("0"="white","1"="#23c8b2") 48 | 49 | basicDark<- "#4f8a83" 50 | 51 | #### 52 | # All defined elements 53 | aesDefs<- list("attendCol8" = attendCol8, 54 | "byearCol5" = byearCol5, 55 | "NACol" = NACol, 56 | "baseSize"= baseSize, 57 | "TIvars"=TIvars, 58 | "TVvars"=TVvars) 59 | 60 | colorFixed <- "blue" 61 | colorRandom <- "red" 62 | -------------------------------------------------------------------------------- /Scripts/Graphs/basicTrajectory.R: -------------------------------------------------------------------------------- 1 | p <- ggplot2::ggplot(dsM,aes(x=time,y=attend, group=id)) 2 | p <- p + geom_line() 3 | p <- p + geom_point(pch=20, size=2.5) 4 | p <- p + plotTheme 5 | p <- p + scale_x_continuous(limits=c(0,11), 6 | breaks=c(0:11)) 7 | p <- p + scale_y_continuous(limits=c(0,8), 8 | breaks=seq(1,8, by=1)) 9 | p <- p + labs(list( 10 | title="How often did you attend worship last year?", 11 | x="Time scale: years since 2000", y="Church attendance")) 12 | -------------------------------------------------------------------------------- /Scripts/Graphs/basicTrajectory300.R: -------------------------------------------------------------------------------- 1 | # p <- ggplot2::ggplot(dsM,aes(x=time,y=attend, group=id)) 2 | # p <- p + geom_line() 3 | # p <- p + geom_point(pch=20, size=2.5) 4 | # p <- p + plotTheme 5 | # p <- p + scale_x_continuous(limits=c(0,11), 6 | # breaks=c(0:11)) 7 | # p <- p + scale_y_continuous(limits=c(1,8), 8 | # breaks=seq(1,8, by=1)) 9 | # p <- p + labs(list( 10 | # title="How often did you attend worship last year?", 11 | # x="Time scale: years since 2000", y="Church attendance")) 12 | 13 | 14 | # dsM <- dplyr::filter(dsL, id <=300, 15 | # raceF != "Mixed (Non-H)") %>% 16 | # dplyr::select(id,sexF,raceF,year,attend,attendF) %>% 17 | # dplyr::mutate(yearc = year - 2000) 18 | # 19 | p <- ggplot2::ggplot(dsM,aes(x=time,y=attend)) 20 | p <- p + geom_line(aes(group=id), color='firebrick', 21 | alpha=.2, 22 | position=position_jitter(w=0.3, h=0.3)) 23 | p <- p + geom_point(shape=1, color="black", fill=NA, 24 | alpha=.4, size=2, 25 | position=position_jitter(w=0.3, h=0.3)) 26 | p <- p + plotTheme 27 | p <- p + scale_x_continuous(limits=c(0,11), 28 | breaks=c(0:11)) 29 | p <- p + scale_y_continuous(limits=c(0,8), 30 | breaks=seq(1,8, by=1)) 31 | p <- p + labs(list( 32 | title="How often did you attend worship last year?", 33 | x="Time scale: years since 2000", y="Church attendance")) 34 | p 35 | -------------------------------------------------------------------------------- /Scripts/Graphs/graphThemes.R: -------------------------------------------------------------------------------- 1 | baseSize <- 12 2 | 3 | theme1 <- ggplot2::theme_bw(base_size=baseSize) + 4 | ggplot2::theme(title=ggplot2::element_text(colour="gray20",size = baseSize+1)) + 5 | ggplot2::theme(axis.text=ggplot2::element_text(colour="gray40", size=baseSize-2)) + 6 | ggplot2::theme(axis.title=ggplot2::element_text(colour="gray40")) + 7 | ggplot2::theme(panel.border = ggplot2::element_rect(colour="gray80")) + 8 | ggplot2::theme(axis.ticks.length = grid::unit(0, "cm")) + 9 | ggplot2::theme(text = element_text(size =baseSize+7)) 10 | 11 | 12 | barFitTheme <- theme_bw() + 13 | theme(axis.text = element_text(colour="gray40", size=15)) + 14 | theme(axis.text.x = element_text(angle=90, vjust = .5)) + 15 | theme(axis.title = element_text(colour="gray40")) + 16 | theme(panel.border = element_rect(colour="gray80")) + 17 | theme(panel.grid.major.x = element_blank()) + 18 | # theme(axis.ticks = element_line(colour="gray80")) + 19 | theme(axis.ticks.length = grid::unit(0, "cm")) + 20 | theme(legend.position=c(.85,.8), legend.justification=c(0,0)) + 21 | # theme(legend.background = element_rect(fill = '#99999933')) + 22 | theme(legend.background = element_rect(fill = NA)) + 23 | theme(legend.text = element_text(colour = 'gray40')) 24 | 25 | 26 | barFitTheme2 <- theme_bw() + 27 | theme(axis.text = element_text(colour="gray40", size=15)) + 28 | theme(axis.text.x = element_text(angle=0, vjust = .5)) + 29 | theme(axis.title = element_text(colour="gray40")) + 30 | theme(panel.border = element_rect(colour="gray80")) + 31 | theme(panel.grid.major.x = element_blank()) + 32 | # theme(axis.ticks = element_line(colour="gray80")) + 33 | theme(axis.ticks.length = grid::unit(0, "cm")) + 34 | theme(legend.position=c(.85,.8), legend.justification=c(0,0)) + 35 | # theme(legend.background = element_rect(fill = '#99999933')) + 36 | theme(legend.background = element_rect(fill = NA)) + 37 | theme(legend.text = element_text(colour = 'gray40')) 38 | -------------------------------------------------------------------------------- /Scripts/Graphs/line_graph_trajectories.R: -------------------------------------------------------------------------------- 1 | # rm(list=ls(all=TRUE)) #Clear the memory of variables from previous run. This is not called by knitr, because it's above the first chunk. 2 | 3 | require(ggplot2) 4 | require(dplyr) 5 | require(reshape2) 6 | 7 | BuildLine <- function( ) { 8 | 9 | baseSize <- 12 10 | ### 11 | plotTheme <- ggplot2::theme_bw() + 12 | ### 13 | ggplot2::theme_bw(base_size=baseSize)+ 14 | ggplot2::theme(title=ggplot2::element_text(colour="gray20",size = baseSize + 3)) + 15 | ggplot2::theme(axis.text=ggplot2::element_text(colour="gray40", size= baseSize - 2))+ 16 | ggplot2::theme(axis.title.x=ggplot2::element_text(colour="gray40", size = baseSize + 2, vjust=-.3))+ 17 | ggplot2::theme(axis.title.y=ggplot2::element_text(colour="gray40", size = baseSize + 2, vjust=1.3))+ 18 | ggplot2::theme(panel.border = ggplot2::element_rect(colour="gray80"))+ 19 | ggplot2::theme(axis.ticks.length = grid::unit(0, "cm"))#+ 20 | # ggplot2::theme(panel.background=element_rect(fill=bgColour,colour=NA)) + 21 | # ggplot2::theme(legend.position=c(.95,.90),legend.direction="vertical") + 22 | # ggplot2::theme(legend.background = element_rect(fill=NA)) + 23 | # ggplot2::theme(legend.text = element_text(size = 15),legend.title.align =(-3.3))# + 24 | # ggplot2::theme(panel.grid = element_line(linetype = 1,size=rel(3))) 25 | dsM<- dsL %>% dplyr::filter(id %in% c(1,23)) 26 | # ds<- dsp 27 | # head(ds) 28 | p <- ggplot2::ggplot(dsM,aes(x=year,y=attend, group=id)) 29 | p <- p + geom_line() + geom_point() + plotTheme 30 | p <- p + scale_x_continuous(limits=c(2000,2011), 31 | breaks=c(2000:2011)) 32 | p <- p + scale_y_continuous(limits=c(1,8), 33 | breaks=seq(1,8, by=1)) 34 | p <- p + labs(list( 35 | title="How often did you attend worship last year?", 36 | x="Year of observation", y="Church attendance")) 37 | p 38 | return( p ) 39 | 40 | } 41 | 42 | gLine <- BuildLine( 43 | p <- p + abline(a=0,b=1)) 44 | print(gLine) 45 | 46 | 47 | # BuildLine("m7F") 48 | # BuildLine("m7R1") 49 | # BuildLine("m7R2") 50 | -------------------------------------------------------------------------------- /Scripts/Utility/InstallPackages.R: -------------------------------------------------------------------------------- 1 | #This code checks the user's installed packages against a list of packages (that we've manually compiled) 2 | # necessary for the graphs to be rendered. Missing packages are installed, while existing packages are not. 3 | # If anyone sees a package that should be on there, please tell me. 4 | rm(list=ls(all=TRUE)) #Clear the memory for any variables set from any previous runs. 5 | 6 | packagesToInstall <- c( 7 | "arm" # for working with model objects, by Gelman & Hill 8 | , "colorspace" #Explicit control over the HCL color scheme 9 | , "devtools" #package development 10 | , "dplyr" # for general data manipulation 11 | , "ggplot2" #Graphing 12 | , "ggthemes" #Extra themes, scales and geoms for ggplot 13 | , "ggmap" #Maps & graphics, based on ggplot 14 | , "googleVis" #JavaScript-based visualizations, like scrollable tables 15 | , "grid" #The underlying framework for the graphics 16 | , "gridExtra" #for table FERE graphs 17 | , "gridBase" #Additional grid functions 18 | , "knitr" #For creating dynamic reports 19 | , "lme4" # used for Random Coefficient Modeling 20 | , "lubridate" #Consistent/convienent function signatures for manipulating dates 21 | , "minqa" 22 | , "nlme" # used for Fixed Effect modeling 23 | , "plyr" #Important for most of our data manipulation 24 | , "psych" # data summary + other useful function 25 | , "RColorBrewer" #Explicit control over the Color Brewer colors. See http://colorbrewer2.org/ 26 | , "reshape2" #Data manipulation not covered in plyr, wide <-> long 27 | , "RJSONIO" # for processing jason files 28 | , "roxygen2" #Creates documentation Rd file from (well-formed) comments 29 | , "RODBC" 30 | , "sas7bdat" # Imports SAS formatted data files 31 | , "stringr" 32 | , "testit" #has the useful `assert()` function 33 | , "testthat" #Heavier testing framework that's good for package development 34 | , "yaml" #for gh-pages production 35 | , "rhdf5" 36 | 37 | ) 38 | 39 | 40 | 41 | 42 | 43 | for( packageName in packagesToInstall ) { 44 | available <- require(packageName, character.only=TRUE) #Loads the packages, and indicates if it's available 45 | if( !available ) { 46 | install.packages(packageName, dependencies=TRUE) 47 | require( packageName, character.only=TRUE) 48 | } 49 | } 50 | 51 | update.packages(ask="graphics", checkBuilt=TRUE) 52 | 53 | #There will be a warning message for every package that's called but not installed. It will look like: 54 | # Warning message: 55 | # In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, : 56 | # there is no package called 'bootstrap' 57 | #If you see the message (either in here or in another piece of the project's code), 58 | # then run this again to make sure everything is installed. You shouldn't get a warning again. -------------------------------------------------------------------------------- /Scripts/Utility/runAll.R: -------------------------------------------------------------------------------- 1 | rm(list=ls(all=TRUE)) 2 | ########## Production of reports from .Rmd files ### 3 | 4 | patternToBuild <- "(?= 90] <- "A+" 8 | grades$letter[percent >= 85 & percent <= 89] <- "A" 9 | grades$letter[percent >= 80 & percent <= 84] <- "A-" 10 | grades$letter[percent >= 77 & percent <= 79] <- "B+" 11 | grades$letter[percent >= 73 & percent <= 76] <- "B" 12 | grades$letter[percent >= 70 & percent <= 72] <- "B-" 13 | grades$letter[percent >= 65 & percent <= 69] <- "C+" 14 | grades$letter[percent >= 60 & percent <= 64] <- "C" 15 | grades$letter[percent >= 50 & percent <= 59] <- "D" 16 | grades$letter[percent < 50 ] <- "F" 17 | detach(grades) 18 | 19 | head(grades) 20 | table(grades$letter) -------------------------------------------------------------------------------- /libs/css/sidebar.css: -------------------------------------------------------------------------------- 1 | #TOC { 2 | position: fixed; 3 | left: 0; 4 | top: 0; 5 | width: 250px; 6 | height: 100%; 7 | overflow:auto; 8 | line-height:200%; 9 | } 10 | 11 | .emphasized { 12 | font-size: 1.2em; 13 | color: red; 14 | } 15 | -------------------------------------------------------------------------------- /psy564.Rproj: -------------------------------------------------------------------------------- 1 | Version: 1.0 2 | 3 | RestoreWorkspace: Default 4 | SaveWorkspace: Default 5 | AlwaysSaveHistory: Default 6 | 7 | EnableCodeIndexing: Yes 8 | UseSpacesForTab: Yes 9 | NumSpacesForTab: 2 10 | Encoding: UTF-8 11 | 12 | RnwWeave: Sweave 13 | LaTeX: pdfLaTeX 14 | --------------------------------------------------------------------------------