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- Title
Modern applications of cross-classified random effects models in social and behavioral research: Illustration with R package PLmixed.
- Authors
Sijia Huang; Minjeong Jeon
- Abstract
Cross-classified random effects models (CCREMs) have been developed for appropriately analyzing data with a cross-classified structure. Despite its flexibility and the prevalence of cross-classified data in social and behavioral research, CCREMs have been under-utilized in applied research. In this article, we present CCREMs as a general and flexible modeling framework, and present a wide range of existing models designed for different purposes as special instances of CCREMs. We also introduce several less well-known applications of CCREMs. The flexibility of CCREMs allows these models to be easily extended to address substantive questions. We use the free R package PLmixed to illustrate the estimation of these models, and show how the general language of the CCREM framework can be translated into specific modeling contexts.
- Subjects
RANDOM effects model; BEHAVIORAL research; GENERALIZABILITY theory
- Publication
Frontiers in Psychology, 2022, Vol 13, p1
- ISSN
1664-1078
- Publication type
Article
- DOI
10.3389/fpsyg.2022.976964