Robust two-stage approach to repeated measurements analysis of chronic ozone exposure in rats

Abstract

A robust two-stage approach is used to reanalyze the repeated measurements from an experiment of airway responsiveness in rats randomized to long-term exposure at four ozone doses. The concentration-response data generated for each rat may be represented as a hierarchical nonlinear model encompasing the sources of variation within and between individual profile for each rat, the conditional modeling approach can assess the adequacy of an assumed mean model, a fundamental advantage not intrinsic to marginal techniques. The two-stage population inference is based on the estimated individual parameters, thus maintaining an intuitive appeal to the toxicologists who traditionally have fitted a separate curve for each animal and then applied ANOVA to the summary statistics. However, we formally adjust the standard errors for the extra variability due to the initial estimation of the individual parameters and also allow for their within-rat correlation. The robust two-stage method appropriately down weights the a berrant responses arising sporadically within individualsand, more importantly, the rats which may be outlying relative to the usual population variation. The true effect of chronic ozone exposure, including a significant gender interaction, may be masked by a few rats which exert undue influence on the population estimates in a nonrobust analysis.