A systematic review of and reflection on the applications of factor mixture modeling

Factor mixture modeling (FMM) incorporates both continuous latent variables and categorical latent variables in a single analytic model clustering items and observations simultaneously. After two decades since the introduction of FMM to psychological and behavioral science research, it is an opportu...

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Vydáno v:Psychological methods Ročník 30; číslo 5; s. 997
Hlavní autoři: Kim, Eunsook, Wang, Yan, Hsu, Hsien-Yuan
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States 01.10.2025
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ISSN:1939-1463, 1939-1463
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Shrnutí:Factor mixture modeling (FMM) incorporates both continuous latent variables and categorical latent variables in a single analytic model clustering items and observations simultaneously. After two decades since the introduction of FMM to psychological and behavioral science research, it is an opportune time to review FMM applications to understand how these applications are utilized in real-world research. We conducted a systematic review of 76 FMM applications. We developed a comprehensive coding scheme based on the current methodological literature of FMM and evaluated common usages and practices of FMM. Based on the review, we identify challenges and issues that applied researchers encounter in the practice of FMM and provide practical suggestions to promote well-informed decision making. Lastly, we discuss future methodological directions and suggest how FMM can be expanded beyond its typical use in applied studies. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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ISSN:1939-1463
1939-1463
DOI:10.1037/met0000630