To date, cross-lagged panel modeling has been studied only for continuous outcomes. This article presents methods that are suitable also when there are binary and ordinal outcomes. Modeling, testing, identification, and estimation are discussed. A two-part ordinal model is proposed for ordinal variables with strong floor effects often seen in applications. An example considers the interaction between stress and alcohol use in an alcohol treatment study. Extensions to multiple-group analysis and modeling in the presence of trends are discussed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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Muthén et al. (2024) studied this question.
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