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1c good entropy sim data.inp
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1c good entropy sim data.inp
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TITLE:
Analysis model uses nominal (latent class) X, binary M, binary Y
Simulating binary X, nominal M and binary Y
Simulating XM interaction effect ON Y by class-varying Y ON X
Step 1: Saving the data for external Monte Carlo analysis
MONTECARLO:
NAMES = y x u1-u5;
CATEGORICAL = y u1-u5;
generate y(1 l) u1-u5(1);
GENCLASSES = c(4);
CLASSES = c(4);
NOBSERVATION = 5000;
SEED = 3454367;
NREPS = 500;
REPSAVE = ALL;
SAVE = sim*.dat;
CUTPOINTS = x(0.841621234); ! 20% exposed
MODEL POPULATION:
%OVERALL%
x@1; ! this is required to render x as a 20% exposure
[c#1*-2.3843] ;
[c#2*-2.1989] ;
[c#3*-1.8194] ;
c#1 ON x*0.9062;
c#2 ON x*1.0181;
c#3 ON x*0.3021;
y ON x*0.553531204;
%c#1%
[u1$1*-2.6 u2$1*-2.6 u3$1*-2.6 u4$1*-2.6 u5$1*-2.6];
[y$1*0.2231];
y ON x*0.6931;
%c#2%
[u1$1*2.6 u2$1*2.6 u3$1*0 u4$1*-2.6 u5$1*-2.6];
[y$1*0.4700];
y ON x*0.7577;
%c#3%
[u1$1*-2.6 u2$1*-2.6 u3$1*0 u4$1*2.6 u5$1*2.6];
[y$1*0.4940];
y ON x*0.4140;
%c#4%
[u1$1*2.6 u2$1*2.6 u3$1*2.6 u4$1*2.6 u5$1*2.6];
[y$1*0.6880];
y ON x*0.4055;
ANALYSIS:
TYPE = MIXTURE;
ESTIMATOR = MLR;
PROC = 4 (STARTS);
MODEL:
%OVERALL%
[c#1*-2.3843] ;
[c#2*-2.1989] ;
[c#3*-1.8194] ;
c#1 ON x*0.9062;
c#2 ON x*1.0181;
c#3 ON x*0.3021;
y ON x*0.553531204;
%c#1%
[u1$1*-2.6 u2$1*-2.6 u3$1*-2.6 u4$1*-2.6 u5$1*-2.6];
[y$1*0.2231];
y ON x*0.6931;
%c#2%
[u1$1*2.6 u2$1*2.6 u3$1*0 u4$1*-2.6 u5$1*-2.6];
[y$1*0.4700];
y ON x*0.7577;
%c#3%
[u1$1*-2.6 u2$1*-2.6 u3$1*0 u4$1*2.6 u5$1*2.6];
[y$1*0.4940];
y ON x*0.4140;
%c#4%
[u1$1*2.6 u2$1*2.6 u3$1*2.6 u4$1*2.6 u5$1*2.6];
[y$1*0.6880];
y ON x*0.4055;