Prefer a chat interface with context about you and your work?
Covariate Decomposition Methods for Longitudinal Missing-at-Random Data and Predictors Associated with Subject-Specific Effects
Investigators often gather longitudinal data to assess changes in responses over time within subjects and to relate these changes to within-subject changes in predictors. Missing data are common in such studies and predictors can be correlated with subject-specific effects. Maximum likelihood methods for generalized linear mixed models provide consistent estimates …