An exponential family model for clustered multivariate binary data

Abstract

This paper focuses on the analysis of clustered multivariate binary data that arise from developmental toxicity studies. In these studies, pregnant mice are exposed to chemicals to assess possible adverse effects on developing fetuses. Multivariate binary outcomes arise when each fetus in a litter is assessed for the presence of malformations and/or low birth weight. We analyse the data using a multivariate exponential family model which is flexible in terms of allowing response rates to depend on cluster size. Maximum likelihood estimation of model parameters and the construction of score tests for dose effect are discussed.