From Sample Average Treatment Effect to Population Average Treatment Effect on the Treated: Combining Experimental with Observational Studies to Estimate Population Treatment Effects
Copyright policy )From Sample Average Treatment Effect to Population Average Treatment Effect on the Treated: Combining Experimental with Observational Studies to Estimate Population Treatment Effects
SummaryRandomized 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.
- University of Cambridge United Kingdom
- University of California, Berkeley United States
- London School of Hygiene & Tropical Medicine United Kingdom
- University of London United Kingdom
randomized controlled trials, external validity, cost-effectiveness studies, placebo tests, causal inference, Applications of statistics, observational studies
randomized controlled trials, external validity, cost-effectiveness studies, placebo tests, causal inference, Applications of statistics, observational studies
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