Incorporating Machine Learning Into Factor Mixture Modeling: Identification of Covariate Interactions to Explain Population Heterogeneity

Incorporating Machine Learning Into Factor Mixture Modeling: Identification of Covariate Interactions to Explain Population Heterogeneity

Factor mixture modeling (FMM) has been widely adopted in health and behavioral sciences to examine unobserved population heterogeneity. Covariates are often included in FMM as predictors of the latent class membership via multinomial logistic regression to help understand the formation and character...

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Bibliographic Details
Main Authors: Yan Wang, Tonghui Xu, Jiabin Shen
Format: Article
Language:English
Published: PsychOpen GOLD/ Leibniz Institute for Psychology 2023-09-01
Series:Methodology
Subjects:
factor mixture model
latent class
machine learning
structural equation model trees
covariate
interaction
Online Access:https://doi.org/10.5964/meth.9487

Internet

https://doi.org/10.5964/meth.9487

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