Classified Mixed Model Projections

J.S. Rao, M. Li and J. Jiang
Journal of the American Statistical Association (to appear)
Black and white portrait of J. Sunil Rao

J. Sunil Rao's interests are in applied statistics, biostatistics, small area estimation and machine learning. His current research focuses on cancer, health disparities and opioid relapse. He has also developed software packages with various students and collaborators.

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Research Interests:

High throughput cancer genomic data modeling;
Health disparity estimation;
Opioid relapse prediction;
Machine learning;
High dimensional modeling; Bayesian model selection; Mixed model selection
and prediction;
Small area estimation; Bump/mode hunting;
Robust estimation;
Precision medicine;
Modeling of
pharmacogenomic data


Software Sites


A statistical technique for detecting differentially expressing genes from microarray data using Bayesian ANOVA

Fence Methods

A class of strategies for selection of fixed and random factors in linear and generalized linear mixed models
MOst Recent

Publications and Articles

Geo-spatial risk factor analysis for drug overdose death in South Florida from 2014-2019, and the independent contribution of social determinants of health

M. Liu, J. Caplan, L. Kennedy, I. Moise, D. Feaster, V. Horigian, J. Roll, S. McPherson and J.S. Rao
Drug and Alcohol Dependence (to appear)

Disparities in Survival due to Social Determinants of Health and Access to Treatment in Operable Malignant Pleural Mesothelioma in the United States

A. Alnajar, S.A. Karen, S.S. Razi, J.S. Rao, K. Gawri, G.D. Lopes, D.M. Nguyen, N. Vllamizar and E. Rodriguez
JAMA Network Open

Comparing Bayesian variable selection to lasso approaches for applications in psychology

S.A. Bainter, T.G. McCauley, M.M. Fahmy, Z.T. Goodman, L.B. Kupis, and J.S. Rao
Psychometrika (to appear)
J. Sunil Rao, Ph.D.

Professor, Division of Biostatistics
School of Public Health
Director of Biostatistics, Masonic Cancer Center
University of Minnesota, Twin Cities

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