Longitudinal models for AIDS marker data

Abstract

Longitudinal Models for AIDS Marker Data W. John Boscardin Jeremy M. G. Taylor Ngayee Law Department of Biostatistics University of California, Los Angeles, USA September 4, 1997 Abstract Over the past decade, researchers have put a great amount of e ort into developing suitable models for the analysis of longitudinal CD4 data and other markers of AIDS progression. These models must be general enough to allow for di erent patterns of change in the marker data. In this paper, we review the existing literature including our preferred models which involve mixed e ects, stochastic terms and in- dependent measurement error. Adding stochastic terms to standard mixed e ects models gives an interpretable and parsimonious method for generalizing the covariance structure of the measurement error and short-term variability. We focus on univariate and bivariate models with Integrated Ornstein-Uhlenbeck IOU stochastic terms. The IOU Address for correspondence: Jeremy M. G. Taylor, Department of Biostatistics, UCLA, Los Angeles, California 90095-1772, USA.