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Variable selection methods for identifying predictor interactions in data with repeatedly measured binary outcomes

INTRODUCTION: Identifying predictors of patient outcomes evaluated over time may require modeling interactions among variables while addressing within-subject correlation. Generalized linear mixed models (GLMMs) and generalized estimating equations (GEEs) address within-subject correlation, but iden...

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Detalles Bibliográficos
Autores principales:	Wolf, Bethany J., Jiang, Yunyun, Wilson, Sylvia H., Oates, Jim C.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Cambridge University Press 2020
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8057419/ https://www.ncbi.nlm.nih.gov/pubmed/33948279 http://dx.doi.org/10.1017/cts.2020.556

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