Title

A latent transition model with logistic regression

Document Type

Article

Date of Original Version

9-1-2007

Abstract

Latent transition models increasingly include covariates that predict prevalence of latent classes at a given time or transition rates among classes over time. In many situations, the covariate of interest may be latent. This paper describes an approach for handling both manifest and latent covariates in a latent transition model. A Bayesian approach via Markov chain Monte Carlo (MCMC) is employed in order to achieve more robust estimates. A case example illustrating the model is provided using data on academic beliefs and achievement in a low-income sample of adolescents in the United States. © 2007 The Psychometric Society.

Publication Title

Psychometrika

Volume

72

Issue

3

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