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Elizabeth A Stuart

Showing results (1-10 of 394) with videos related to

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Statistical Science : a Review Journal of the Institute of Mathematical Statistics|September 28, 2010
Matching methods for causal inference: A review and a look forwardElizabeth A Stuart
Statistics in Medicine|February 21, 2008
Developing practical recommendations for the use of propensity scores: discussion of 'A critical appraisal of propensity score matching in the medical literature between 1996 and 2003' by Peter Austin, Statistics in MedicineElizabeth A Stuart
Evaluation Review|August 6, 2016
Generalizing Treatment Effect Estimates From Sample to Population: A Case Study in the Difficulties of Finding Sufficient DataElizabeth A Stuart, Anna Rhodes
Statistical Methods in Medical Research|October 6, 2011
Assessing the sensitivity of methods for estimating principal causal effectsElizabeth A Stuart, Booil Jo
The American Journal of Clinical Nutrition|February 23, 2019
Best (but oft-forgotten) practices: missing data methods in randomized controlled nutrition trialsPeng Li, Elizabeth A Stuart
Harvard Data Science Review|December 5, 2025
Expanding the Data Science Toolkit: Mixed Methods for Improving Causal InferenceNoor Qaragholi, Elizabeth A Stuart
Statistics in Medicine|July 18, 2009
On the use of propensity scores in principal causal effect estimationBooil Jo, Elizabeth A Stuart
JAMA Pediatrics|September 8, 2020
Study Designs and Statistical Methods for Studies of Child and Adolescent Health PoliciesBenjamin French, Elizabeth A Stuart
Epidemiologic Reviews|June 10, 2021
Matching Methods for Confounder Adjustment: An Addition to the Epidemiologist's ToolboxNoah Greifer, Elizabeth A Stuart
American Journal of Epidemiology|October 10, 2017
Using Sensitivity Analyses for Unobserved Confounding to Address Covariate Measurement Error in Propensity Score MethodsKara E Rudolph, Elizabeth A Stuart
Pageof 40

Showing results (1-10 of 394) with videos related to

Sort By:
Pageof 40
Statistical Science : a Review Journal of the Institute of Mathematical Statistics|September 28, 2010
Matching methods for causal inference: A review and a look forwardElizabeth A Stuart
Statistics in Medicine|February 21, 2008
Developing practical recommendations for the use of propensity scores: discussion of 'A critical appraisal of propensity score matching in the medical literature between 1996 and 2003' by Peter Austin, Statistics in MedicineElizabeth A Stuart
Evaluation Review|August 6, 2016
Generalizing Treatment Effect Estimates From Sample to Population: A Case Study in the Difficulties of Finding Sufficient DataElizabeth A Stuart, Anna Rhodes
Statistical Methods in Medical Research|October 6, 2011
Assessing the sensitivity of methods for estimating principal causal effectsElizabeth A Stuart, Booil Jo
The American Journal of Clinical Nutrition|February 23, 2019
Best (but oft-forgotten) practices: missing data methods in randomized controlled nutrition trialsPeng Li, Elizabeth A Stuart
Harvard Data Science Review|December 5, 2025
Expanding the Data Science Toolkit: Mixed Methods for Improving Causal InferenceNoor Qaragholi, Elizabeth A Stuart
Statistics in Medicine|July 18, 2009
On the use of propensity scores in principal causal effect estimationBooil Jo, Elizabeth A Stuart
JAMA Pediatrics|September 8, 2020
Study Designs and Statistical Methods for Studies of Child and Adolescent Health PoliciesBenjamin French, Elizabeth A Stuart
Epidemiologic Reviews|June 10, 2021
Matching Methods for Confounder Adjustment: An Addition to the Epidemiologist's ToolboxNoah Greifer, Elizabeth A Stuart
American Journal of Epidemiology|October 10, 2017
Using Sensitivity Analyses for Unobserved Confounding to Address Covariate Measurement Error in Propensity Score MethodsKara E Rudolph, Elizabeth A Stuart
Pageof 40