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


Hartman, E; Grieve, R; Ramsahai, R; Sekhon, JS; (2015) From sample average treatment effect to population average treatment effect on the treated: combining experimental with observational studies to estimate population treatment effects. Journal of the Royal Statistical Society: Series A (Statistics in Society). n/a-n/a. ISSN 1467-985X DOI: https://doi.org/10.1111/rssa.12094

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Abstract

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.

Item Type: Article
Keywords: Causal inference, Cost-effectiveness studies, External validity, Observational studies, Placebo tests, Randomized controlled trials
Faculty and Department: Faculty of Public Health and Policy > Dept of Health Services Research and Policy
Research Centre: Centre for Statistical Methodology
URI: http://researchonline.lshtm.ac.uk/id/eprint/2130309

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