My main research is in the development of statistical methodology of doing family studies. I am concentrating on three important areas: 1) statistical models for analysis in genetic (family based) data; 2) development of statistical methods that deal with ascertainment bias; and 3) the examination of gene-environment and gene-gene interactions that may be involved in the etiology of breast, colorectal, or prostate cancer. Applications of my research include the use of efficient designs that allow for the testing of hypotheses concerning gene-environment interactions or effect modifications related to the etiology of breast, ovarian, and colon cancer; estimation of the frequency of susceptibility or metabolic genes in the general population; and the estimation of the attributable risk of genetic and environmental factors for breast, ovarian, and colorectal cancer. Other areas of interest include analysis of epidemiologic studies of cancer and other chronic diseases. In particular, I am interested in the development of efficient sampling for the analysis of case-control and cohort studies as applied to the genetic epidemiology. These designs include nested case-control, case-cohort, and counter-match case control designs. My interest is in determining the efficiency of such designs and comparing the relative efficiency across different study designs. Other research interests include developing methods of correction for measurement error in case-control and cohort studies. In particular, I am concerned with situations where information on exposure data (measured and true) exists in part of the subjects but not in all participants. Another area related to the above is m interest in developing statistical methods for family validation studies.