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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...
Autores principales: | Kim, Soyoung, Jeong, Yoonhwa, Hong, Sehee |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
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 |
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