Grant: Discovery Grants Program - Individual

The principal objective of my research is to develop and evaluate statistical methodology that may be usefully applied to the health sciences. Most of this research involves the development of methods that may be applied when standard statistical techniques are inappropriate, due to the violation of underlying assumptions An example of this is my past and continuing research on methods of analysis for the design and cluster randomization trials, experimental studies which allocate intact social units rather than individuals to different intervention groups. These trials have become increasingly popular over the past fifteen years, particularly in the evaluation of educational programs and innovations in the provision of health care. Since individuals within a cluster cannot be regarded as statistically independent, standard methods of analysis do not apply, and could result in misleading conclusions. Much of my research in this area has been focused on the development of methods that take into account within-cluster dependencies in such a way that the resulting inferences have valid and efficient statistical priorities. My textbook published in 2000, entitled ""Design and Analysis of Cluster Randomization Trials in Health Research,"" co-authored with Dr. Neil Klar, summarizes much of mypublished research in this field. A Chinese translation of our text was published in 2006. A second area of my research involves the development of inference methods for assessing interobserver agreement in samples of small to moderate size. Although the kappa statistic is widely used in both psychology and the health sciences to measure interobserver agreement, traditional methods for significance-testing and confidence interval construction require sample sizes that are frequently beyond the range available to many investigators. My overall objective is to develop a unified framework for inferences concerning interobserver agreement in designs that accommodates multiple replicates per subject in studies having more than two raters and several outcome categories. Virtually all the problems I address emanate from my experience as a biostatistician collaborating with researchers in the Health Sciences.