Finding latent groups in observed data: A primer on latent profile analysis in Mplus for applied researchers

作者：Sarah L. Ferguson, E. Whitney G. Moore, Darrell M. Hull · 发表于：International Journal of Behavioral Development · 年份：2019 · DOI：10.1177/0165025419881721 · 被引用次数：902 · 研究领域：Forest ecology and management、Statistical Methods and Bayesian Inference、Bayesian Methods and Mixture Models

The present guide provides a practical guide to conducting latent profile analysis (LPA) in the Mplus software system. This guide is intended for researchers familiar with some latent variable modeling but not LPA specifically. A general procedure for conducting LPA is provided in six steps: (a) data inspection, (b) iterative evaluation of models, (c) model fit and interpretability, (d) investigation of patterns of profiles in a retained model, (e) covariate analysis, and (f) presentation of results. A worked example is provided with syntax and results to exemplify the steps.