//LG5.1// version = 5.1 infile 'exercise-1-latentgold-data.csv' delim = comma quote = single model title '4-class_Missing_MAR'; options maxthreads=8; algorithm tolerance=1e-008 emtolerance=0.01 emiterations=250 nriterations=50 ; startvalues seed=0 sets=16 tolerance=1e-005 iterations=50; bayes categorical=0 variances=1 latent=0 poisson=1; montecarlo seed=239497 sets=0 replicates=500 tolerance=1e-008; quadrature nodes=10; missing includeall; //include output option MARchi2 for G2 based on Missing at Random assumption output parameters=effect betaopts=wl standarderrors profile probmeans=posterior bivariateresiduals estimatedvalues=model MARchi2 reorderclasses; variables dependent LIFETIME, PREV_YR, PREV_MO, NEXT_MO, APRV_TRY, APRV_OCC, APRV_REG; latent Cluster nominal 4; equations Cluster <- 1; LIFETIME <- 1 + Cluster; PREV_YR <- 1 + Cluster; PREV_MO <- 1 + Cluster; NEXT_MO <- 1 + Cluster; APRV_TRY <- 1 + Cluster; APRV_OCC <- 1 + Cluster; APRV_REG <- 1 + Cluster; end model model title '4-class_Missing_MCAR'; options maxthreads=8; algorithm tolerance=1e-008 emtolerance=0.01 emiterations=250 nriterations=50 ; startvalues seed=0 sets=16 tolerance=1e-005 iterations=50; bayes categorical=0 variances=1 latent=0 poisson=1; montecarlo seed=239497 sets=0 replicates=500 tolerance=1e-008; quadrature nodes=10; missing includeall; // Omit output option MARchi2 for G2 based on Missing Completely at Random assumption // Compute G2(MCAR) - G2(MAR) to test MCAR (Chi-square difference test) output parameters=effect betaopts=wl standarderrors profile probmeans=posterior bivariateresiduals estimatedvalues=model reorderclasses; variables dependent LIFETIME, PREV_YR, PREV_MO, NEXT_MO, APRV_TRY, APRV_OCC, APRV_REG; latent Cluster nominal 4; equations Cluster <- 1; LIFETIME <- 1 + Cluster; PREV_YR <- 1 + Cluster; PREV_MO <- 1 + Cluster; NEXT_MO <- 1 + Cluster; APRV_TRY <- 1 + Cluster; APRV_OCC <- 1 + Cluster; APRV_REG <- 1 + Cluster; end model