From sample average treatment effect to population average treatment effect on the treated: combining experimental with observational studies to estimate population treatment effects

Randomized controlled trials (RCTs) can provide unbiased estimates of sample average treatment effects. However, a common concern is that RCTs may fail to provide unbiased estimates of population average treatment effects. We derive the assumptions that are required to identify population average tr...

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Bibliographic Details
Published in:Journal of the Royal Statistical Society. Series A, Statistics in society Statistics in society, 2015-06, Vol.178 (3), p.757-778
Main Authors: Hartman, Erin, Grieve, Richard, Ramsahai, Roland, Sekhon, Jasjeet S.
Format: Article
Language:English
Subjects:
Average
Causal inference
Clinical trials
Cost effectiveness analysis
Cost efficiency
Cost-effectiveness
Cost-effectiveness studies
Entropy
Estimation
Estimation bias
External validity
Intubation
Medical treatment
Observational studies
Placebo tests
Placebos
Political action committees
Population
Population distributions
Population estimates
Pulmonary arteries
Pulmonary artery catheterization
Randomized controlled trials
Sample surveys
Side effects
Statistics
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Summary:Randomized controlled trials (RCTs) can provide unbiased estimates of sample average treatment effects. However, a common concern is that RCTs may fail to provide unbiased estimates of population average treatment effects. We derive the assumptions that are required to identify population average treatment effects from RCTs. We provide placebo tests, which formally follow from the identifying assumptions and can assess whether they hold. We offer new research designs for estimating population effects that use non-randomized studies to adjust the RCT data. This approach is considered in a cost-effectiveness analysis of a clinical intervention: pulmonary artery catheterization.
ISSN:0964-1998
1467-985X
DOI:10.1111/rssa.12094