The models presented here require longitudinal data (i.e., data that are collected at two or more occasions). Code is available for models such as latent transition analysis (LTA), repeated measures LCA (RMLCA), and associative latent transition analysis (ALTA), among others.

LTA: Baseline Latent Transition Analysis with Categorical Indicators

This code fits a 4-class, latent-class model for marijuana use and attitudes using 7 binary indicators of the latent class variable. It includes a grouping variable for year, and observations came from 3 different years. Measurement invariance across groups is imposed such that analogous item-response probabilities within classes are restricted to be equal to each other across groups.

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