Analysis of clustered binary data with covariates specific to each observation

Abstract

The standard approach for analysis of teratology studies is to use a population-averaged model with primary interest on evaluating dose-response effects. For example, generalized estimating equations (GEEs) have become popular for analysis of both developmental toxicity and reproductive studies (Ryan 1992). Such an approach is typically appropriate since the covariate of interest-exposure level-is constant for each litter of animals. Recently, however, there has been growing interest in evaluating effects of covariates that can vary between individuals within a cluster. This article explores several opportunities generated by teratology studies with individual-level covariates both in terms of modeling approaches and in decomposition of litter effects into genetic and environmental components.