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Sander Greenland

Professor Emeritus


DepartmentsType of Faculty
Contact Information

UCLA School of Public Health
Department of Epidemiology
Box 951772. 71-279A CHS
Los Angeles, CA 90095

Areas of Interest: 

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

Sander Greenland is Professor of Epidemiology and Statistics at the University of California, Los Angeles. He received Bachelor's and Master's degrees in mathematics and Master's and Doctoral degrees in Epidemiology from the University of California. Since then he has become a leading contributor to epidemiologic statistics, theory, and methods. His focus has been the limitations and misuse of statistical methods in observational studies. He has authored or co-authored over 300 articles in epidemiology, statistics, and medical journals, and co-authored the textbook Modern Epidemiology. He is a Fellow of the American Statistical Association and the Royal Statistical Society. He has served as an associate editor for several statistics and epidemiology journals, as an advisor for the Food and Drug Administration, the Environmental Protection Agency, the Centers for Disease Control, the State of California, and the National Academy of Sciences, and has been an invited speaker at universities and conferences throughout the world.


MS., Public Health, University California, Los Angeles
Dr. PH., Epidemiology, University of California, Los Angeles
Selected Publications: 

Greenland S Transparency and disclosure, neutrality and balance: shared values or just shared words?. J Epid Community Health 2012; 66: in press.

Greenland S, Pearl J Adjustments and their consequences. Int Stat Review 2011; 79: 401-426.

Greenland S, Poole C Problems in common interpretations of statistics in scientific articles, expert reports, and testimony. Jurimetrics 2011; 51: 113-29.

Greenland S Simpon's paradox from adding constants in contingency tables. Am Stat 2010; 64: 340-4.

Greenland S The need for sycretism in applied statistics. Stat Science 2010; 25: 158-61.

Greenland S Bayesian perspectives for epidemiologic research. III. Bias analysis via missing-data methods. International Journal of Epidemiology 2009; 38: 1662-1673.

Greenland S Dealing with uncertainty about investigator bias. J Epidemiol Community Health 2009; 63: 593-598.

Greenland S, Kheifets L Designs and analyses for exploring the relation of magnetic fields to childhood leukaemia: A pilot project for the Danish National Birth Cohort. Scand J Public Health 2009; 37: 83-92.

Greenland S Interactions in epidemiology: relevance, identification, estimation . Epidemiology 2009; 14-17.

Greenland S Relaxation penalties and priors for plausible modeling of nonidentified biases. Statistical Science 2009; 24: 195-210.

Greenland S Weaknesses of certain Bayesian methods for meta-analysis. Clinical Trials 2009; 6: 42-46.

Greenland S, Lanes SF, Jara M Estimating efficacy from randomized trials with discontinuations: The need for intent-to-treat design and g-estimation. Clinical Trials 2008; 5: 5-13.

Greenland S Variable selection and shrinkage in the control of confounders. Am J Epid 2008; 167: 523-529.

Greenland S. Bayesian perspectives for epidemiologic research. II. Regression analysis. Int J Epidemiol 2007; 36: 195-202.

Greenland S Maximum-likelihood and closed-form estimators of epidemiologic measures under misclassification. J Statist Planning and Inference 2007; 138: 528-538.

Greenland S. Prior data for non-normal priors. Stat Med 2007; 26: 3578-3590.

Greenland Sander Nonsignificance plus high power does not imply support for the null over the alternative.. Annals of epidemiology. 2012; 22(5): 364-8.

Greenland Sander Null misinterpretation in statistical testing and its impact on health risk assessment.. Preventive medicine. 2011; 53(4-5): 225-8.