The Center for Health Statistics was established in 2001 to provide a statistical research environment that would lead to advances in the design and analysis of investigations in a wide variety of areas in the health sciences. Under the direction of Dr. Robert D. Gibbons, the Center has quickly grown to include a faculty of 13 members both from the University of Illinois at Chicago (UIC) and in collaboration with other Universities.

Within the first two years, the Center has obtained three Federal grants for statistical research from the NIH amounting to several million dollars. The overall goal of the Center is to provide foundational statistical research that will further scientific applications in areas of Health Services Research, Mental Health, Neuroimaging, Genomics, and Environmental sciences.

Key statistical themes in our work include (a) mixed-effects regression models for the analysis of clustered and longitudinal data, (b) analysis of observational data, (c) problems in the analysis of high-dimensional datasets that are encountered in fMRI and microarray studies, (d) application of item response theory and computerized adaptive testing to problems in mental health measurement, (e) analysis of multivariate binary data, (f) interlaboratory calibration, and (g) interval estimation including prediction, tolerance, and confidence intervals for environmental monitoring problems.

The Center benefits greatly from rich collaborations with faculty at UIC, NIH, and research scientists across the country. We have a particularly close association with the Department of Psychiatry at UIC and several other leading departments of Psychiatry across the country. Some of the products of our work are distributed freely over the Internet as a series of computer programs developed under the direction of Don Hedeker in collaboration with Dave Patterson and his colleagues at Discerning Systems in Vancouver. The site is widely utilized by applied researchers and statisticians around the world, with close to 100 unique visits per day.

Overall, we are committed to working on statistical features of any interesting scientific problem, and our excellent faculty provide the depth of resources to accomplish this goal.