Evaluating Covariate Effects on ESM Measurement Model Changes with Latent Markov Factor Analysis: A Three-Step Approach

• Published in: Multivariate behavioral research Vol. 58; no. 2; pp. 262 - 291
• Main Authors: Vogelsmeier, Leonie V.D.E., Vermunt, Jeroen K., Bülow, Anne, De Roover, Kim
• Format: Journal Article
• Language: English
• Published: United States Routledge 04.03.2023; Taylor & Francis Ltd
• Subjects: Between-subjects design; Clustering; Data Interpretation, Statistical; Empirical analysis; Evaluation; Experience sampling; Factor analysis; Humans; Invariance; latent Markov modeling; Markov Chains; measurement invariance; Mixtures; Psychological factors; three-step approach; Time Factors; factor analysis; Experience sampling; measurement invariance; three-step approach; latent Markov modeling

Invariance of the measurement model (MM) between subjects and within subjects over time is a prerequisite for drawing valid inferences when studying dynamics of psychological factors in intensive longitudinal data. To conveniently evaluate this invariance, latent Markov factor analysis (LMFA) was pr...