Comparing Bayesian random coefficient prediction and latent interaction models for multilevel moderated mediation

These findings highlight the robustness of Bayesian approaches in handling complex hierarchical data, particularly in educational and psychological research. Future research should explore additional factors, such as measurement error and more complex moderator structures, to enhance our understanding of Bayesian multilevel modeling.

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Publication Details

Journal
Frontiers in Psychology
Published
2026-03-05
DOI
https://doi.org/10.3389/fpsyg.2025.1543330
Primary Topic
Psychometric Methodologies and Testing
Type
article
Field-Weighted Citation Impact
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article

Comparing Bayesian random coefficient prediction and latent interaction models for multilevel moderated mediation

SoYoung Kim, Sooyong Lee
Frontiers in Psychology
Psychometric Methodologies and Testing
article

Comparing Bayesian random coefficient prediction and latent interaction models for multilevel moderated mediation

SoYoung Kim, Sooyong Lee
article en

Abstract

These findings highlight the robustness of Bayesian approaches in handling complex hierarchical data, particularly in educational and psychological research. Future research should explore additional factors, such as measurement error and more complex moderator structures, to enhance our understanding of Bayesian multilevel modeling.

Frontiers in PsychologyVol. 16
Chonnam National University (KR), University of Wisconsin System (US), University of Wisconsin–Madison (US)
Openalex Percentile: Top 39%
Psychometric Methodologies and Testing
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