Departments of Medicine, Health Studies, and Psychiatry
Robert Gibbons is a statistician interested in the areas of biostatistics, environmental statistics, and psychometrics. Major themes in his work include development of linear and nonlinear mixed effects regression models for analysis of longitudinal data, analysis of environmental monitoring data and inter-laboratory calibration, item response theory and computerized adaptive testing, and the development of new statistical methods in pharmacoepidemiology and drug safety.
He is an elected member of the Institute of Medicine of the National Academy of Sciences and a fellow of the American Statistical Association.
Gibbons has coauthored many publications, including “Full-Information Item Bi-Factor Analysis,” “Waiting for Organ Transplantation,” and “Weighted Random-Effects Regression Models with Application to Inter-Laboratory Calibration.”
He earned his PhD in statistics and psychometrics from the University of Chicago and his BA in chemistry and mathematics from the University of Denver.
Gibbons joined the University of Chicago faculty in 2011.