Robust Regression Analysis of Longitudinal Data under Censoring

Abstract

We consider regression analysis of longitudinal data when the temporal correlation is modeled by an autoregressive process. Robust R estimators of regression and autoregressive parameters are obtained. Our estimators are valid under censoring caused by detection limits. Efficient computation of the estimators is discussed. Theoretical and simulation studies of the estimators are presented. We analyze a real data set on air pollution using our methodology.