The models presented here are considered “baseline” in the sense that they do not add features such as grouping variables, covariates, or outcomes. These are the simplest versions of LCA, LPA, mixed indicator models, and LTA.

LCA: Baseline LCA with 3+ level categorical indicators

This code fits a longitudinal latent class model, using categorical indicators with 3+ levels, to identify latent classes indicated by multidimensional experiences of racism and heterosexism during the transition to adulthood among sexual minority men of color.

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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