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From sample average treatment effect to population average treatment effect on the treated: combining experimental with observational studies to estimate population treatment effects
Author(s) -
Hartman Erin,
Grieve Richard,
Ramsahai Roland,
Sekhon Jasjeet S.
Publication year - 2015
Publication title -
journal of the royal statistical society: series a (statistics in society)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.103
H-Index - 84
eISSN - 1467-985X
pISSN - 0964-1998
DOI - 10.1111/rssa.12094
Subject(s) - observational study , randomized controlled trial , average treatment effect , sample size determination , treatment effect , population , randomized experiment , medicine , treatment and control groups , statistics , placebo , mathematics , surgery , propensity score matching , alternative medicine , environmental health , traditional medicine , pathology
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.