Brumback, Babette

Associate Chair for Education & ProfessorFACULTY_BrumbackBabette

Department of Biostatistics
College of Public Health & Health Professions College of Medicine
University of Florida
2004 Mowry Rd., Rm. 5244
P.O. Box 117450
Gainesville, FL 32611-7450


  • PhD, Statistics, University of California, Berkeley 1996
  • MA, Statistics, University of California, Berkeley 1992
  • BS, Electrical Engineering, University of Virginia, Charlottesville 1988

Professional Biography

Babette Brumback, Ph.D., is Professor and Associate Chair of the Department of Biostatistics at the University of Florida.  Her statistical research has concentrated on methods for longitudinal data analysis, causal modeling, bias adjustment, and analysis of data from complex sampling designs.  She has also collaborated extensively on public health and medical studies concerning a broad array of research areas.   Her professional activities include serving in 2015 as Chair of the American Statistical Association Section on Statistics in Epidemiology, serving in 2015—2016 as President of the Florida Chapter of the American Statistical Association, serving from 2011-2015 as a member of the National Institutes of Health Study Section on Clinical and Integrative Cardiovascular Sciences, and serving in 2016-2017 on an Advisory Panel for the MMS Program of the National Science Foundation.  She has also served as Associate Editor of Biometrics and as Statistical Editor of Psychosomatic Medicine.  Dr. Brumback received her PhD in Statistics from the University of California, Berkeley in 1996, followed by postdoctoral training in Biostatistics and Epidemiology at the Harvard School of Public Health from 1996-1999.  She is an elected member of Delta Omega and a Fellow of the American Statistical Association.


  • Causal modeling and inference for clinical trials and observational studies
  • Longitudinal data analysis
  • Penalized spline models
  • Random effects models / Multilevel models
  • Health survey sampling design and analysis
  • Methods for handling missing data
  • Bias adjustments for observational data analysis
  • General biostatistical methods
  • Statistical methods in epidemiology
  • Statistical applications in public health and medicine