Robert Greevy
PhD, Statistics, University of Pennsylvania
Research interests include: restricted randomization methods and sample size adaptive randomization for clinical trials, inverse probability weighted and doubly robust estimators, sensitivity analyses for unmeasured confounding, foundational tools for better statistical inference, comparative effectiveness of anti-hyperglycemic medications in an EHR derived cohort of 400 thousand veterans with type 2 diabetes, effects of acute kidney injury in an EHR derived cohort of 17 million veterans, randomized controlled trials for smoking cessation and for diabetes management
More information: biostat.app.vumc.org/RobertGreevy
Robert Greevy teaches the first year graduate course 'Principles of Modern Biostatistics'. His statistical methods research interests include: restricted randomization methods and sample size adaptive randomization for clinical trials, inverse probability weighted and doubly robust estimators, sensitivity analyses for unmeasured confounding, and foundational tools for better statistical inference. His medical research interests include: comparative effectiveness of anti-hyperglycemic medications in an EHR derived cohort of 400 thousand veterans with type 2 diabetes, effects of acute kidney injury in an EHR derived cohort of 17 million veterans, and randomized controlled trials for smoking cessation and for diabetes management.