Professional Summary
Mousumi Banerjee is a Research Associate Professor in the Department of Biostatistics. She received her Ph.D. in Statistics from the University of Wisconsin-Madison. Her previous appointments include Assistant Professor at the State University of New York in Buffalo, and at Wayne State University, and Associate Professor at Wayne State University. She also held visiting faculty appointments at the University of Pretoria and the University of Calcutta. Dr. Banerjee's current research interests include tree-structured regression and ensemble methods for censored data, survival analysis with competing risks, and multilevel models in health services research applications. She is also a member of the UM Comprehensive Cancer Center.
Courses Taught
BIOSTAT 560: Statistical Methods for Epidemiology BIOSTAT 664: Statistical Methods for Cancer Research
Education
Ph.D., Statistics, University of Wisconsin, Madison, 1994
M.S., Statistics, Indian Statistical Institute, Calcutta, India, 1988
B.S., Statistics, Indian Statistical Institute, Calcutta, India, 1986
Research Interest & Projects
My methodological research interest is in tree-based methods for survival data. This is motivated by the need of clinical researchers to define interpretable prognostic classification rules both for understanding the prognostic structure of data and for designing future clinical trials. I also work on statistical models and methods for analyzing competing risks data. In this context, I have been particularly interested in situations where the exact cause of death is only partially known. Finally, I am interested in longitudinal data methods, with a focus on model diagnostics and goodness of fit procedures. My applied research has focused on studies using data from population-based cancer registries to investigate disparities in patterns of cancer care and outcomes, with an emphasis on racial and ethnic disparities.
Selected Publications
Banerjee M, Noone A.M. (2008). Tree-Based Methods for Survival Data. In M. Segal, S. Datta, J. Fine (Ed.) Statistical Advances in Biomedical Sciences: State of the Art and Future Directions (265-285). Wiley: New York..
Miller, D.C., Saigal, C.S., Banerjee, M., Hanley, J., Litwin, M.S. (2008). Diffusion of Surgical Innovation Among Patients with Kidney Cancer. Cancer, 112, 1708-1717.
Banerjee, M., George, J., Yee, C., Hryniuk, W., Schwartz, K. (2007). Disentangling the Effects of Race on Breast Cancer Treatment Cancer, 110, 2169-2177.
Banerjee M., George J., Song E.Y., Roy A., and Hrynuik W. (2004). Tree-Based Model for Breast Cancer Prognostication. Journal of Clinical Oncology, 22, 2567-2575.
Basu S., Sen A., and Banerjee M. (2003). Bayesian Analysis of Competing Risks with Partially Masked Cause-of-failure. Journal of the Royal Statistical Society, Series C: Applied Statistics, 52, 77-93.
Basu S., Banerjee M., and Sen A. (2000). Bayesian Inference for Kappa from Single and Multiple Studies. Biometrics, 56, 577-582.
Banerjee M., Biswas D., Sakr W., and Wood D.P. Jr. (2000). Recursive Partitioning for Prognostic Grouping of Patients with Clinically Localized Prostate Cancer. Cancer, 89, 404-411.
Banerjee M. and Frees E.W. (1997). Influence Diagnostics for Linear Longitudinal Models. Journal of the American Statistical Association, 92, 999-1005.
Professional Affiliations
American Statistical Association
International Biometric Society
International Indian Statistical Association
American Association for Cancer Research
|
Site Menu
back to top