Sander Greenland, Dr.P.H.

A Short Biography:

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.


Work Titles
UCLA Professor Emeritus, Statistics Professor Emeritus, Epidemiology
Education:
Degrees:
Dr.P.H., University of California, Los Angeles
M.A., University of California, Berkeley
M.S., University California, Los Angeles

Contact Information:

Detailed Biography:

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 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.

Publications:

A selected list of publications:

Greenland Sander   Analysis goals, error-cost sensitivity, and analysis hacking: essential considerations in hypothesis testing and multiple comparisons, Pediatric and Perinatal Epidemiology, 2021; 35: 8-23.
Greenland S, Fay MP, Brittain EH, Shih JH, Follmann DA, Gabriel EE, Robins, JM   On causal inferences for personalized medicine: How hidden causal assumptions led to erroneous causal claims about the D-value, The American Statistician , 2020; 74: 243-248.
Greenland, Sander   Valid P-values behave exactly as they should: Some misleading criticisms of P-values and their resolution with S-values The American Statistician, 2019; 73(Supplement 1): 106-114.
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Greenland S   Bayesian perspectives for epidemiologic research. I, Int J Epidemiol , 2006; 35: 765-78.
Greenland S   Smoothing observational data: a philosophy and implementation for the health sciences, Int Statist Rev, 2006; 74: 31-46.
Greenland S   Multiple-bias modeling for analysis of observational data, J Royal Stat Soc A, 2005; 168: 267-308.
Greenland Sander   Invited Commentary: The Need for Cognitive Science in Methodology American journal of epidemiology, 2017; 186(6): 639-645.
Greenland Sander   For and Against Methodologies: Some Perspectives on Recent Causal and Statistical Inference Debates European journal of epidemiology, 2017; 32(1): 3-20.
Greenland Sander, Mansournia Mohammad Ali, Altman Douglas G   Sparse data bias: a problem hiding in plain sight BMJ (Clinical research ed.), 2016; 352(39): i1981.
Greenland Sander, Daniel Rhian, Pearce Neil   Outcome modelling strategies in epidemiology: traditional methods and basic alternatives International journal of epidemiology, 2016; 45(2): 565-75.
Greenland Sander, Senn Stephen J, Rothman Kenneth J, Carlin John B, Poole Charles, Goodman Steven N, Altman Douglas G   Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations European journal of epidemiology, 2016; 31(4): 337-50.
Greenland Sander, Mansournia Mohammad Ali   Penalization, bias reduction, and default priors in logistic and related categorical and survival regressions Statistics in medicine, 2015; 34(23): 3133-43.
Greenland Sander   Concepts and pitfalls in measuring and interpreting attributable fractions, prevented fractions, and causation probabilities Annals of epidemiology, 2015; 25(3): 155-61.
Greenland Sander, Pearce Neil   Statistical foundations for model-based adjustments Annual review of public health, 2015; 36(4): 89-108.
Greenland S, Poole C   Living with P values: resurrecting a Bayesian perspective on frequentist statistics, Epidemiology, 2013; 24: 62-8.
Greenland S, Poole C   Living with statistics in observational research, Epidemiology, 2013; 24: 73-8.
Greenland Sander   Cornfield, risk relativism, and research synthesis Statistics in medicine, 2012; 31(24): 2773-7.
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.
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 Sander   Accounting for uncertainty about investigator bias: disclosure is informative Journal of epidemiology and community health, 2009; 63(8): 593-8.
Greenland S   Bayesian perspectives for epidemiologic research. III. Bias analysis via missing-data methods, International Journal of Epidemiology, 2009; 38: 1662-1673.
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 Sander   Weaknesses of Bayesian model averaging for meta-analysis in the study of vitamin E and mortality Clinical trials (London, England), 2009; 6(1): 42-6; discussion 50-1.
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, Gustafson Paul   Accounting for independent nondifferential misclassification does not increase certainty that an observed association is in the correct direction American journal of epidemiology, 2006; 164(1): 63-8.

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