Read about latent class analysis or latent transition analysis. option to generate 20 random draws for each individual’s class membership based on posterior probabilities.indication of which latent class is the best match for each individual, and.ability to assess identification of models with covariates via multiple random starts,.accounts for sampling weights and clusters.optional Bayesian stabilizing prior to handle sparseness issues in estimation,.parameter estimates saved to SAS data file,.posterior probabilities saved to SAS data file,. baseline-category multinomial logit model or binary logit model for prediction,.LCA and LTA with covariates (prediction of latent class membership and transitions),.These straightforward procedures make it possible to pre-process data, fit a variety of latent class and latent transition models, and post-process the results without leaving the SAS environment. PROC LCA and PROC LTA are SAS procedures for latent class analysis (LCA) and latent transition analysis (LTA) developed by the Methodology Center. PROC LCA is intended for individual installations and is not tested for server installations of SAS or for SAS University Edition.
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