Pages 145-146
In clinical studies, correlated binary response data are frequently collected. Although various methods for analysis of correlated data have been proposed, the evaluation on those is not sufficient in case of binary responses with specifically various missing mechanisms. Therefore we investigated the performance of six statistical methods (last observation carried forward (LOCF), complete case analysis (CC), conventional generalized estimating equations (GEE), weighted-GEE (WGEE), multiple imputation (MI) and generalized linear mixed-effects models (GLMM)) for correlated binary response with missing. Continuous variables for defining binary responses were used to impute missing values in MI and to calculate the weights for WGEE. This evaluation used actual data from a clinical study that compared two antidepressants.
