Bayesian analysis of multiple responses from an animal carcinogen mixture experiment

Abstract

An 18-month chronic bioassay was conducted using ICR mice to determine whether health hazards are associated with exposure to a mixture of chlorinated alkanes and alkenes (CA) with composition similar to the contaminated water from drinking wells near an abandoned RCA factory. All test animals died spontaneously or sacrificed were examined to evaluate the influence of the CA mixture on the incidence of mammary gland tumor development, tumor size, and event of uterine enlargement. In this paper, we propose trinomial/lognormal mixture models for modeling two dichotomous and one continuous outcomes simultaneously. Monte Carlo methods based on Markov chains are used for the models which are built in a Bayesian framework. Bayesian inferences on odds of these multiple events and also the survivorship of these events for the CA mixture exposure groups are presented.