J Clin Transl Sci 2020 Nov 16;5(1):e59. Epub 2020 Nov 16.
Department of Medicine, Division of Rheumatology and Immunology, Medical University of South Carolina, Charleston, SC, USA.
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 identifying interactions can be difficult if not hypothesized . We evaluate the performance of several variable selection approaches for clustered binary outcomes to provide guidance for choosing between the methods. Read More