The purpose of this project is to develop new statistical methods for, and to apply new and existing statistical techniques in, the analysis of data from laboratory animal studies. Special emphasis is placed on the type of data arising in the National Toxicology Program (NTP) carcinogenesis bioassays. Much of my research time is spent working on new statistical solutions to practical problems which are important to NTP scientists. In addition, some of my research time is devoted to applying these new procedures to the specific data which originally motivated the work on methods development. Finally, the remainder of my research time is spent applying existing statistical procedures, sometimes in novel ways, to data collected by collaborators here at the National Institute of Environmental Health Sciences (NIEHS).? ? Some of my methodological research is summarized in Dr. Shyamal Peddada's project entitled 'Statistical Methods with Applications to Toxicology and Microarray Data' (Z01-ES-101744). However, the majority of my research relates primarily to the development of new methods in three areas: (1) nonparametric hazard analysis with missing cause-of-death data, (2) inference about shape-constrained hazard functions, and (3) accounting for body weight in causal inference about tumor incidence. The first method is based on kernel smoothing techniques, while the other two methods are developed in a Bayesian framework and use Markov Chain Monte Carlo (MCMC) computational techniques. These three areas of research are described in more detail below.
