协变量
潜变量
可解释性
潜在类模型
潜变量模型
心理学
语法
结构方程建模
统计
计算机科学
自然语言处理
人工智能
机器学习
数学
作者
Sarah L. Ferguson,E. Whitney G. Moore,Darrell M. Hull
标识
DOI:10.1177/0165025419881721
摘要
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.
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