A semi-parametric regression analysis of CD4 cell counts.
This paper considers the regression analysis of CD4 cell counts, a commonly used indicator and prognostic factor of AIDS progression. For this purpose, a number of methods have been proposed and most of them are based on random effects models. We present an alternative that is based on a mean function regression model. The new method is more natural and particularly appropriate if population parameters such as treatment comparison are mainly of interest. To estimate regression parameters, we present an estimating equation-based approach, which does not require estimation of the baseline mean function. This makes the implementation of the approach and the study of the properties of the estimated regression parameters much easier than those based on random effects models. The method is illustrated with a set of CD4 cell count data arising from an AIDS clinical trial and simulated data.
Sun
J
J
Department of Statistics, University of Missouri, 222 Math Sciences Building, Columbia, Missouri 65211, USA. tsun@stat.missouri.edu
D000163:Acquired Immunodeficiency Syndrome / Q000276:immunology; D001699:Biometry; D018791:CD4 Lymphocyte Count / Q000706:statistics & numerical data*; D006801:Humans; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data; D012044:Regression Analysis