Roee Gutman is an Associate Professor of Biostatistics at Brown. Dr. Gutman’s areas of research interest are Bayesian data analysis, missing data, matching, file linkage, causal inference and bioinformatics. His work in matching and file linkage addresses problems with combining administrative and clinical data having common elements in which privacy regulations limit access to unique identifiers. Dr. Gutman uses missing data techniques to assess uncertainty in the match probabilities and thus develops statistically valid procedures. His work in causal inference seeks to obtain valid comparisons of non-randomized interventions that appropriately adjust for differences in baseline covariates by applying advanced regression modeling techniques to multiply impute the missing potential outcomes. He has applied these methods for linking causes of deaths from vital statistics mortality files with end-of-life medical costs obtained from Medicare and Medicaid Services and to link release records of HIV+ prisoners with Ryan White clinical records, as well as to compare opioids and NSAIDS after motor vehicle crashes, estimate effects of bed-hold policy in nursing homes on mortality and hospitalization and estimate the effect of erythropoietin-stimulating agents on patients with end-stage renal disease.

Roee received his Ph.D. from the Department of Statistics at Harvard University. His advisor was Professor Donald Rubin and he was a member of Professor Jun Liu's lab. His Ph.D. thesis is entitled: "Topics in Missing Data and Causality." Roee received a BS with Honors in Statistics, Operations Research and Computer Science from Tel Aviv University (TAU) in 1999. He went on to receive a MS in Applied Statistics with Special Honors under the supervision of Professor Yossef Hochberg from TAU.