Mousumi Banerjee, Ph.D.

Mousumi Banerjee

Research Professor of Biostatistics

Director of Biostatistics, Center for Healthcare Outcomes & Policy (CHOP)

M4150, SPH II      Vcard icon
1415 Washington Heights
Ann Arbor, Michigan 48109-2029

SPH: (734) 764-5451; CHOP: (734)-615-7137; Fax: (734)-763-2215


Curriculum Vitae (PDF)

Professional Summary

Mousumi Banerjee is Research Professor in the Department of Biostatistics and Director of Biostatistics at the Center for Healthcare Outcomes and Policy (CHOP). She is also a member of the University of Michigan Comprehensive Cancer Center. Dr. Banerjee received her BStat and MStat degrees in Statistics from the Indian Statistical Institute in Calcutta, India and her PhD in Statistics from the University of Wisconsin-Madison. Before joining the University of Michigan, she held faculty appointments at the State University of New York in Buffalo, and at Wayne State University in Detroit. Dr. Banerjee also held visiting faculty appointments at the University of Pretoria in South Africa and the University of Calcutta in India. Her methodological research focuses on tree-structured regression and ensemble methods, multilevel models, longitudinal analyses, survival analyses, and competing risks; with applications to cancer epidemiology and health services research. Dr. Banerjee has served as Principal Investigator of methodology as well as applied grants from the National Science Foundation, National Institutes of Health, and the Department of Defense. She is also involved as a co-investigator in numerous R01s with faculty in the Cancer Center, Surgery, Urology, and Internal Medicine. She is a Fellow of the American Statistical Association, and an elected member of the International Statistical Institute.

Courses Taught

BIOSTAT524: Biostatistics for Clinical Researchers    Syllabus (PDF)
BIOSTAT581: Longitudinal Models and Repeated Measures    Syllabus (PDF)

BIOSTAT 560: Statistical Methods for Epidemiology

BIOSTAT 664: Statistical Methods for Cancer Research

BIOSTAT 653: Applied Statistics III ANOVA and Linear Mixed Models


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 Interests & Projects

My methodological research interest is in tree-based regression and ensemble 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 multilevel data modelling, 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.

Selected Publications

Search PubMed for publications by Mousumi Banerjee >>

Haymart MR, Banerjee M, Stewart AK, Koenig RJ, Birkmeyer JD, Griggs JJ. (2011). Use of Radioactive Iodine for Thyroid Cancer Journal of the American Medical Association, 306, 721-728.

Banerjee M., Ding Y., Noone A.M (2012). Identifying Representative Trees from Ensembles Statistics in Medicine.

Zhao L, Banerjee M. (2012). Bayesian Piecewise Mixture Model for Racial Disparity in Prostate Cancer Progression Computational Statistics and Data Analysis, 56, 362-369.

Filson C.P., Banerjee M., Wolf S. Jr., Ye Z., Wei J.T., Miller D.C. (2011). Surgeon Characteristics and Long-term Trends in the Adoption of Laparoscopic Radical Nephrectomy Journal of Urology, 185, 2072-2077.

Sen A., Banerjee M., Li Y., Noone A.M. (2010). A Bayesian Approach to Competing Risks with Masked Cause of Death Statistics in Medicine, 29, 1681-1695.

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.

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
International Statistical Institute

Recent News Items

  • "Black Women Get Less Breast Cancer Treatment," Washington Post, October 08, 2007
  • "Racial Disparities Affect Breast Cancer Treatment,", October 08, 2007