Sander Greenland

Sander Greenland is Emeritus Professor of Epidemiology and Statistics at UCLA. He received honors Bachelor's and Master's degrees in Mathematics from the University of California Berkeley where he was Regent's and National Science Foundation Fellow in Mathematics, followed by Master's and Doctoral degrees in Epidemiology from UCLA where he was Regent's Fellow in Epidemiology. He became Professor of Epidemiology in the UCLA Fielding School of Public Health in 1989 and Professor of Statistics in the UCLA College of Letters and Science in 1999. He was made a Fellow of the Royal Statistical Society in 1993, a Fellow of the American Statistical Association in 1998, and was given an honorary doctorate by Aarhus University in 2013. He has published over 400 scientific papers and book chapters, and co-authored a leading advanced textbook on epidemiology. His many contributions to statistics and epidemiology include causal inference, bias analysis, and meta-analysis methods, with a focus on extensions, limitations, and misuses of statistics in nonexperimental studies, especially in postmarketing surveillance of drugs, vaccines, and medical devices. He has served on the editorial boards of many statistics and epidemiology journals, as an advisor for the World Health Organization, the U.S. Food and Drug Administration, the Environmental Protection Agency, the Centers for Disease Control, and the National Academy of Sciences, and has been an invited speaker at universities and conferences throughout the world. 

View CV


  • DrPH, Epidemiology, University of California, Los Angeles, CA
  • MS, Public Health, University California, Los Angeles, CA
  • MA, Mathematics, University of California, Berkeley, CA
  • BA, Mathematics, University of California, Berkeley, CA

Areas of Interest

Epidemiologic methodology; statistical methods for epidemiologic data; epidemiologic assessment of medicines and medical technology; foundations of nonexperimental inference. 


  • Greenland S (ed.) (1987). Evolution of Epidemiologic Ideas: Annotated Readings on Concepts and Methods. Chestnut Hill, MA: Epidemiology Resources Inc. 

  • Rothman KJ, Greenland S (1998). Modern Epidemiology, 2nd ed. Philadelphia: Lippincott-Raven. 

  • Porta MS, Greenland S, Last JM (eds). (2008). A Dictionary of Epidemiology, 5th ed. New York: Oxford University Press. 

  • Rothman KJ, Greenland S, Lash TL (2008). Modern Epidemiology, 3rd ed. Philadelphia: Lippincott-Wolters-Kluwer. 

Selected Publications

  • Greenland S. Multiple-bias modeling for analysis of observational data. J Royal Stat Soc A 2005; 168; 267-308. 

  • Greenland S. Bayesian perspectives for epidemiologic research, part I. Int J Epidemiol 2006; 35: 765-78. 

  • Greenland S, Gustafson P. Adjustment for independent nondifferential misclassification does not increase certainty that an observed association is in the correct direction. Am J Epidemiol 2006; 164: 63-8. 

  • Greenland S. Smoothing observational data: a philosophy and implementation for the health sciences. Int Statist Rev 2006; 74: 31-46. 

  • Greenland S. Bayesian perspectives for epidemiologic research, part II. Int J Epidemiol 2007; 36: 195-202. 

  • Greenland S. Prior data for non-normal priors. Stat Med 2007; 26: 3578-90. 

  • Greenland S. Maximum-likelihood and closed-form estimators of epidemiologic measures under misclassification. J Statist Planning Inference2007; 138: 528-38. 

  • Greenland S. Variable selection and shrinkage in the control of confounders. Am J Epidemiol 2008; 167: 523-9. 

  • Greenland S, Kheifets L. Designs and analyses for exploring the relation of magnetic fields to childhood leukemia. Scand J Public Health 2009; 37: 83-92. 

  • Greenland S. Interactions in epidemiology: relevance, identification, estimation. Epidemiology 2009; 20: 14-7. 

  • Greenland S. Dealing with uncertainty about investigator bias. J Epid Community Health 2009;63: 593-8. 

  • Greenland S. Weaknesses of Bayesian model averaging for meta-analysis in the study of vitamin E and mortality. Clin Trials 2009; 6:42-6. 

  • Greenland S. Bayesian perspectives for epidemiologic research, part III. Int J Epidemiol2009; 38: 1662-73. 

  • Greenland S. Relaxation penalties and priors for plausible modeling of nonidentified bias sources. Stat Science 2009; 24: 195-210. 

  • Greenland S. Simpson’s paradox from adding constants in contingency tables as an example of Bayesian noncollapsibility. The American Statistician 2010; 64:340-4. 

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