Detecting Conditional Dependence Using Flexible Bayesian Latent Class Analysis

Detecting Conditional Dependence Using Flexible Bayesian Latent Class Analysis

A fundamental assumption underlying latent class analysis (LCA) is that class indicators are conditionally independent of each other, given latent class membership. Bayesian LCA enables researchers to detect and accommodate violations of this assumption by estimating any number of correlations among...

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Bibliographic Details
Main Authors: Jaehoon Lee, Kwanghee Jung, Jungkyu Park
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-08-01
Series:Frontiers in Psychology
Subjects:
conditional dependence
Bayesian latent class analysis
approximate independence
prior variance
model fit
Online Access:https://www.frontiersin.org/article/10.3389/fpsyg.2020.01987/full

Internet

https://www.frontiersin.org/article/10.3389/fpsyg.2020.01987/full

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