Examining Population Heterogeneity in Finite Mixture Settings Using Latent Variable Modeling

被引:5
作者
Raykov, Tenko [1 ]
Marcoulides, George A. [2 ]
Chang, Chi [1 ]
机构
[1] Michigan State Univ, E Lansing, MI 48824 USA
[2] Univ Calif Santa Barbara, Santa Barbara, CA 93106 USA
关键词
conditional independence; latent class analysis; model selection; single-class model; unobserved heterogeneity; within-class model;
D O I
10.1080/10705511.2015.1103193
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
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.
引用
收藏
页码:726 / 730
页数:5
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