2023 - Research.com Mathematics in United States Leader Award
1998 - Fellow of the American Statistical Association (ASA)
Sander Greenland spends much of his time researching Statistics, Confounding, Econometrics, Confidence interval and Odds ratio. Statistics is a component of his Covariate, Logistic regression, Estimator, Regression and Regression analysis studies. His Confounding study also includes fields such as
His studies in Econometrics integrate themes in fields like Inference and Bayesian probability, Bayes' theorem. The Confidence interval study combines topics in areas such as Sample size determination, Meta-analysis, Mean squared error, Point estimation and Monte Carlo method. Surgery is closely connected to Case-control study in his research, which is encompassed under the umbrella topic of Odds ratio.
The scientist’s investigation covers issues in Statistics, Econometrics, Confounding, Confidence interval and Internal medicine. His study in Estimator, Odds ratio, Logistic regression, Bayesian probability and Covariate is carried out as part of his Statistics studies. His Econometrics research incorporates themes from Regression analysis and Observational study.
A large part of his Confounding studies is devoted to Confounding Factors. His research in Confidence interval is mostly focused on Relative risk. His Internal medicine research is multidisciplinary, relying on both Gastroenterology and Oncology.
Sander Greenland mainly investigates Statistics, Econometrics, Confidence interval, Statistical hypothesis testing and Confounding. His multidisciplinary approach integrates Statistics and Sensitivity in his work. His Econometrics research is multidisciplinary, incorporating elements of Uncertainty analysis, Prior probability, Bayesian probability and Identification.
Sander Greenland interconnects Null hypothesis, Alternative hypothesis, Dosing and Statistical power in the investigation of issues within Confidence interval. His study in Statistical hypothesis testing is interdisciplinary in nature, drawing from both Statistical inference, Inference, Interpretation and Scientific communication. Sander Greenland has researched Confounding in several fields, including Treatment outcome, Outcome, Regression, Causal inference and Measure.
His main research concerns Statistics, Inference, Confounding, Econometrics and Covariate. His Inference research focuses on subjects like p-value, which are linked to Interpretation, Statistical power and Confidence interval. His Confounding research focuses on Odds ratio and how it connects with Protocol and Matching.
His studies in Econometrics integrate themes in fields like Logistic regression, Prior probability, Bayesian probability, Representation and Graphical model. The Prior probability study which covers Regression analysis that intersects with Sample size determination. His research investigates the connection between Covariate and topics such as Artificial intelligence that intersect with problems in Causal inference and Outcome.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Causal diagrams for epidemiologic research.
Sander Greenland;Judea Pearl;James M. Robins.
Modern Epidemiology 3rd edition
Kenneth J. Rothman DrPH;Timothy L. Lash;Sander Greenland;Kenneth J. Rothman.
Modeling and variable selection in epidemiologic analysis.
American Journal of Public Health (1989)
THE IMPACT OF CONFOUNDER SELECTION CRITERIA ON EFFECT ESTIMATION
Ruth M. Mickey;Sander Greenland.
American Journal of Epidemiology (1989)
Simulation Study of Confounder-Selection Strategies
George Maldonado;Sander Greenland.
American Journal of Epidemiology (1993)
Methods for Trend Estimation from Summarized Dose-Response Data, with Applications to Meta-Analysis
Sander Greenland;Matthew P. Longnecker.
American Journal of Epidemiology (1992)
Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations
Sander Greenland;Stephen J. Senn;Kenneth J. Rothman;John B. Carlin.
European Journal of Epidemiology (2016)
Scientists rise up against statistical significance
Valentin Amrhein;Sander Greenland;Blake McShane.
QUANTITATIVE METHODS IN THE REVIEW OF EPIDEMIOLOGIC LITERATURE
Epidemiologic Reviews (1987)
Identifiability and exchangeability for direct and indirect effects.
James M. Robins;Sander Greenland.
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