The Impact of Ignoring a Crossed Factor in Cross-Classified Multilevel Modeling

The present study investigated estimate biases in cross-classified random effect modeling (CCREM) and hierarchical linear modeling (HLM) when ignoring a crossed factor in CCREM considering the impact of the feeder and the magnitude of coefficients. There were six simulation factors: the magnitude of...

Descripción completa

Detalles Bibliográficos
Autores principales: Kim, Soyoung, Jeong, Yoonhwa, Hong, Sehee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Psychology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7965978/
https://www.ncbi.nlm.nih.gov/pubmed/33746856
http://dx.doi.org/10.3389/fpsyg.2021.637645

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7965978/
https://www.ncbi.nlm.nih.gov/pubmed/33746856
http://dx.doi.org/10.3389/fpsyg.2021.637645

Ejemplares similares