Center & Institute Affiliations
Scott L. Zeger, PhD, MS, develops statistical methods for longitudinal studies, focusing on Bayesian estimation of disease state, trajectory and likely benefits of interventions.
biostatistics; environmental statistics; epidemiologic statistics; Bayesian statistics; hierarchical models; longitudinal data analysis; regression analysis; time series analysis; international health
Experiences & Accomplishments
University of Pennsylvania
My methodologic research is to develop statistical models that support scientific learning about human health. My earlier work was on regression models for correlated responses that arise when observations come in clusters, for example in longitudinal research or in sample surveys or when data are observed over time or space. We have extended generalized linear models (logistic, linear, log-linear and survival models) to be applicable in these cases. More recently, my work has been on Bayesian models for "individualized health", that is to use population data to improve decisions about an individual's health state, trajectory or likely benefits and costs of competing interventions. We have applied our novel methods to estimate the etiology of children's pneumonia, trajectory of mental disorders and to predict whether a man's prostate cancer is indolent or aggressive.
Honors & Awards
John C. Malone Professor of Biostatistics and Medicine Karl Pearson Award (with Kung-Yee Liang) from the International Statistical Institute, 2015 Honorary Doctoral Degree, University of Lancaster (School of Medicine), 2015 Samuel S. Wilks Award. American Statistical Association, 2008 Marvin Zelen Leadership Award in Statistical Science, 2007 Bradford Hill Medal, Royal Statistical Society, 2007 Member, National Academy of Sciences’ Institute of Medicine, 2006 Golden Apple Award, 2006, 2002, 1988 Ernest Lyman Stebbins Medal,1996 Spiegelman Award, 1991 Snedecor Award from American Statistical Association (with Kung-Yee Liang, 1986-1987
- Books/Monographs: Diggle PJ, Heagerty P, Liang KY, and Zeger SL. The Analysis of Longitudinal Data. Oxford, England: 2nd edition. Oxford University Press, 2002.
- Liang K-Y, Zeger SL: Longitudinal data analysis using generalized linear models. Biometrika 73(1):13-22, 1986.
- Zeger SL, Wyant T, Miller LS, Samet J: Statistical testimony on damages in Minnesota v. Tobacco Industry. In: Statistical Science in the Courtroom. Gastwirth J, editor. New York: Springer-Verlag, 2000.
- Wu Z, Casciola-Rosen L, Shah A, Rosen A, Zeger SL. Estimating autoantibody signatures to detect autoimmune disease patient subsets. Biostatistics. PMID: 29140482, 2017.
- Fiksel, J., Datta, A., Amouzou, A. and Zeger, S., 2021. Generalized bayes quantification learning under dataset shift. Journal of the American Statistical Association, pp.1-19
Pneumonia Etiology Research for Children's Health (PERCH)
National Evaluation Program
Johns Hopkins Individualized Health Initiative (Hopkins inHealth)
Bayesian Hierarchical Models for Individualized Health
Cookstore Replacement for Prevention of ARI and Low Birthweight in Nepal
Nepal Cookstove Replacement Trial
Developing Bayesian analytical approaches to estimation of pneumonia etiology
Countrywide Mortality Surveillance for Action COMSA
Prioritization of modifiable risk factors for adverse pregnancy outcomes and neonatal mortality in rural Nepal
Johns Hopkins Rheumatic Diseases Resource-based Core Center
PERCH: etiology of pneumonia in 7 African and Asian countries
COVID-19 Vaccine Effectiveness: global review
Global Impact of PCV on invasive pneumococcal disease in all ages (PSERENADE)