BIOSTAT 601: Probability and Distribution Theory
BIOSTAT 602: Biostatistical Inference
BIOSTAT 653: Applied Statistics III: ANOVA and Linear Mixed Models
BIOSTAT 802: Advanced Inference II
- PhD, Statistics, University of Wisconsin, Madison, 1993
- M.S., Statistics, Indian Statistical Institute, Calcutta, India, 1987
- B.S., Statistics, Indian Statistical Institute, Calcutta, India, 1985
Research Interests & Projects
- My primary area of methodological research is analysis of recurrent event data in both biomedical and engineering contexts. I also work in the areas of competing risks, accelerated failure time modeling, and agreement measures as it pertains to biomarker research. As a faculty in the Department of Family Medicine, I am heavily involved in collaborative projects in a variety of topics including health services research, management of mental health, cancer prevention through behavioral intervention and lifestyle modification. As a primary biostatistician supporting the work of the GI oncology group at the University of Michigan Rogel Cancer Center, my applied collaborations have focused on studies of biomarker discovery and dietary interventions in gastrointestinal cancers.
Sen A, Banerjee M, Li Y, Noone AM. A Bayesian approach to competing risks analysis with masked cause of death. Stat Med, 29(16):1681-95, 2010.
Sen A, Lee S-Y, Gillespie BW, Kazerooni EA, Goodsitt MM, Rosenman KD, Lockey JE, Meyer CA, Petsonk EL, Wang ML, Franzblau A. Comparing film and digital radiographs for reliability of pneumoconiosis classifications: A modeling approach. Acad Radiol, 17(4):511-19, 2010.
Sen A, Ren J, Ruffin MT, Turgeon DK, Brenner DE, Sidahmed E, Rapai ME, Cornellier ML, Djuric, Z. Relationships between serum and colon concentrations of carotenoids and fatty acids in randomized dietary intervention trial. Cancer Prev Res, 6(6):558-65, 2013. PMCID: PMC4021591
Fries A, Cherry P, Easterling, R, Elsayed E, Huzurbazar, A, Jacobs P, Meeker WQ, Nagappan N, Pecht M, Sen A, Van Der Weil S; for the Panel on Reliability Growth Methods for Defense Systems, On behalf of Panel on Reliability Growth Methods for Defense Systems. Reliability Growth: Enhancing Defense System Reliability. National Research Council.Committee on National Statistics, Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academy Press, 2014.
Samboonsavatdee A, Sen A. Statistical inference for power law process with competing risks. Technometrics, 57(1):112-22, 2015.
Somboonsavatdee A, Sen A. Parametric inference for multiple repairable systems under dependent competing risks. Appl Stoch Models Bus Ind, 31(5):706-20, 2015.
Satagopan JM, Sen A, Zhou Q, Qing L, Rothman N, Langseth H, Engel LS. Bayes and empirical Bayes methods for reduced rank regression models in matched case-control studies. Biometrics, 72(2):584-95, 2016. PMCID: PMC4870158
Zick SM, Sen A, Wyatt GK, Murphy SL, Arnedt JT, Harris RE. Investigation of 2 types of self-administered acupressure for persistent cancer-related fatigue in breast cancer survivors: a randomized clinical trial. JAMA Oncol, 2(11):1470-76, 2016.
Jimbo M, Sen A, Plegue MA, Hawley ST, Kelly-Blake K, Rapai M, Zhang M, Zhang Y, Xie X, Ruffin MT. Interactivity in a decision aid? Findings from a Decision Aid to Technologically Enhance Shared Decision Making RCT. Am J Prev Med, 57(1):77-86, 2019.
Boonstra, PS, Barbaro, RP, Sen A. Default Priors for the Intercept Parameter in Logistic Regressions. Comput Stat Data Anal, 133: 245-256, 2019.
- American Statistical Association
- Internationall Biometric Society
- International Indian Statistical Association
- International Statistical Institute