Examining Population Heterogeneity in Finite Mixture Settings Using Latent Variable Modeling

作者：Raykov Tenko^*; Marcoulides George A; Chang Chi

来源：Structural Equation Modeling, 2016, 23(5): 726-730.

DOI：10.1080/10705511.2015.1103193

• conditional independence
• latent class analysis
• model selection
• single-class model
• unobserved heterogeneity
• within-class model

A latent variable modeling procedure for examining whether a studied population could be a mixture of 2 or more latent classes is discussed. The approach can be used to evaluate a single-class model vis-a-vis competing models of increasing complexity for a given set of observed variables without making any assumptions about their within-class interrelationships. The method is helpful in the initial stages of finite mixture analyses to assess whether models with 2 or more classes should be subsequently considered as opposed to a single-class model. The discussed procedure is illustrated with a numerical example.

• 出版日期2016-10