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Laura B Balzer

Showing results (1-10 of 95) with videos related to

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Epidemiology (Cambridge, Mass.)|March 28, 2017
"All Generalizations Are Dangerous, Even This One."-Alexandre DumasLaura B Balzer
The New England Journal of Medicine|July 25, 2020
Randomization versus Real-World EvidenceLaura B Balzer, Francesca Dominici
American Journal of Epidemiology|July 16, 2021
Demystifying Statistical Inference When Using Machine Learning in Causal ResearchLaura B Balzer, Ted Westling
American Journal of Epidemiology|March 22, 2021
Invited Commentary: Machine Learning in Causal Inference-How Do I Love Thee? Let Me Count the WaysLaura B Balzer, Maya L Petersen
Epidemiology (Cambridge, Mass.)|December 15, 2021
State-Level Masking Mandates and COVID-19 Outcomes in the United States: A Demonstration of the Causal RoadmapAngus K Wong, Laura B Balzer
American Journal of Epidemiology|January 9, 2023
A Demonstration of Modified Treatment Policies to Evaluate Shifts in Mobility and COVID-19 Case Rates in US CountiesJoshua R Nugent, Laura B Balzer
European Journal of Epidemiology|April 12, 2018
Stacked generalization: an introduction to super learningAshley I Naimi, Laura B Balzer
Epidemiology (Cambridge, Mass.)|May 31, 2023
Start with the Target Trial Protocol, Then Follow the Roadmap for Causal InferenceLauren E Dang, Laura B Balzer
International Journal of Environmental Research and Public Health|January 26, 2021
Examining Obedience Training as a Physical Activity Intervention for Dog Owners: Findings from the Stealth Pet Obedience Training (SPOT) Pilot StudyKatie Potter, Brittany Masteller, Laura B Balzer
Statistics in Medicine|January 19, 2022
Causal inference methods for vaccine sieve analysis with effect modificationGuandong Yang, Laura B Balzer, David Benkeser
Pageof 10

Showing results (1-10 of 95) with videos related to

Sort By:
Pageof 10
Epidemiology (Cambridge, Mass.)|March 28, 2017
"All Generalizations Are Dangerous, Even This One."-Alexandre DumasLaura B Balzer
The New England Journal of Medicine|July 25, 2020
Randomization versus Real-World EvidenceLaura B Balzer, Francesca Dominici
American Journal of Epidemiology|July 16, 2021
Demystifying Statistical Inference When Using Machine Learning in Causal ResearchLaura B Balzer, Ted Westling
American Journal of Epidemiology|March 22, 2021
Invited Commentary: Machine Learning in Causal Inference-How Do I Love Thee? Let Me Count the WaysLaura B Balzer, Maya L Petersen
Epidemiology (Cambridge, Mass.)|December 15, 2021
State-Level Masking Mandates and COVID-19 Outcomes in the United States: A Demonstration of the Causal RoadmapAngus K Wong, Laura B Balzer
American Journal of Epidemiology|January 9, 2023
A Demonstration of Modified Treatment Policies to Evaluate Shifts in Mobility and COVID-19 Case Rates in US CountiesJoshua R Nugent, Laura B Balzer
European Journal of Epidemiology|April 12, 2018
Stacked generalization: an introduction to super learningAshley I Naimi, Laura B Balzer
Epidemiology (Cambridge, Mass.)|May 31, 2023
Start with the Target Trial Protocol, Then Follow the Roadmap for Causal InferenceLauren E Dang, Laura B Balzer
International Journal of Environmental Research and Public Health|January 26, 2021
Examining Obedience Training as a Physical Activity Intervention for Dog Owners: Findings from the Stealth Pet Obedience Training (SPOT) Pilot StudyKatie Potter, Brittany Masteller, Laura B Balzer
Statistics in Medicine|January 19, 2022
Causal inference methods for vaccine sieve analysis with effect modificationGuandong Yang, Laura B Balzer, David Benkeser
Pageof 10