The analysis of cancer chemoprevention experiments

This paper is concerned with the analysis of certain cancer chemoprevention experiments that involve Type I censoring. In experiments of this nature, two common response variables are the number of induced cancers and the rate at which they develop. In this study we assume that the number of induced tumors and their times to detection are described by the Poisson and gamma distributions, respectively. Using the method of maximum likelihood, we discuss a procedure for estimating the parameters characterizing these two distributions. We apply standard techniques in order to construct a confidence region and conduct a hypothesis test concerning the parameters of interest. We discuss a method for comparing the effects of two different treatments using the likelihood ratio principle. A technique for isolating group differences in terms of the mean number of promoted tumors and the mean time to detection is described. Using the techniques developed in this paper, we reanalyze an existing data set in the cancer chemoprevention literature and obtain contrasting results.