This code adds a binary and a continuous outcome to the 4-class baseline LCA model with all binary indicators. This code uses the automated 3-step BCH approach as we explore the association between latent class membership and each outcome.

This code adds a binary and a continuous outcome to the 4-class baseline LCA model with all binary indicators. This code uses the the manual 3-step BCH approach as we explore the association between latent class membership and each outcome.

This code demonstrates how to use a latent class moderator to examine heterogeneity in intervention effects among adolescents receiving treatment for cannabis use. First, the code identifies latent classes of contextual and individual risk at baseline using LCA. Then, it uses an adjusted 3-step approach with BCH weights to regress the outcomes on level of care, latent class membership, the interaction between them, and covariates.

This code fits a baseline, latent-profile model to identify and describe profiles of financial stress responses. It also imposes measurement invariance across the groups with means and variances equal.