Mplus Users Guide v6.. - Muthén & Muthén

CHAPTER 7u1u2cu3u4In this example, the latent class analysis (LCA) model with binary latentclass indicators shown in the picture above is estimated using automaticstarting values and random starts. Because c is a categorical latentvariable, the interpretation of the picture is not the same as for modelswith continuous latent variables. The arrows from c to the latent classindicators u1, u2, u3, and u4 indicate that the thresholds of the latentclass indicators vary across the classes of c. This implies that theprobabilities of the latent class indicators vary across the classes of c.The arrows correspond to the regressions of the latent class indicators ona set of dummy variables representing the categories of c.The CATEGORICAL option is used to specify which dependentvariables are treated as binary or ordered categorical (ordinal) variablesin the model and its estimation. In the example above, the latent classindicators u1, u2, u3, and u4, are binary or ordered categorical variables.The program determines the number of categories for each indicator.The AUXILIARY option is used to specify variables that are not part ofthe analysis for which equalities of means across latent classes will betested using posterior probability-based multiple imputations. The lettere in parentheses is placed behind the variables in the auxiliary statementfor which equalities of means across latent classes will be tested.152