Partially Recursively Induced Structured Moderation (PRISM) for a deeper understanding of the complexity of racial differences in endometrial cancer survival

J.S. Rao, E. Kobetz, H. Yu, J. Baeker-Bispo and Z. Bailey

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


Implements a unified treatment of the “Bump Hunting” task in high-dimensional space.
MOst Recent

Publications and Articles


A simple correction for COVID-19 sampling bias

D. Diaz and J.S. Rao
Journal of Theoretical Biology 

Mode Hunting using Pettiest Components Analysis

T. Liu, D. Diaz, J.S. Rao and J.E. Dazard

Identifying causal moderators of disparity subtypes using balanced recursive partitioning

J.S. Rao and C. Conversano
J. Sunil Rao, Ph.D.

Professor and Director, Division of Biostatistics
Miller School of Medicine, University of Miami

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