The use of propensity scores and observational data to estimate randomized controlled trial generalizability bias
Although randomized controlled trials are considered the ‘gold standard’ for clinical studies, the use of exclusion criteria may impact the external validity of the results. It is unknown whether estimators of effect size are biased by excluding a portion of the target population from enrollment. We...
Saved in:
Published in | Statistics in medicine Vol. 32; no. 20; pp. 3552 - 3568 |
---|---|
Main Authors | , |
Format | Journal Article |
Language | English |
Published |
England
Blackwell Publishing Ltd
10.09.2013
Wiley Subscription Services, Inc |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Although randomized controlled trials are considered the ‘gold standard’ for clinical studies, the use of exclusion criteria may impact the external validity of the results. It is unknown whether estimators of effect size are biased by excluding a portion of the target population from enrollment. We propose to use observational data to estimate the bias due to enrollment restrictions, which we term generalizability bias. In this paper, we introduce a class of estimators for the generalizability bias and use simulation to study its properties in the presence of non‐constant treatment effects. We find the surprising result that our estimators can be unbiased for the true generalizability bias even when all potentially confounding variables are not measured. In addition, our proposed doubly robust estimator performs well even for mis‐specified models. Copyright © 2013 John Wiley & Sons, Ltd. |
---|---|
Bibliography: | ArticleID:SIM5802 ark:/67375/WNG-JK7PF1RQ-9 istex:C0C9AC52F2D65ECE10E865FA4239723133B4A1AF ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0277-6715 1097-0258 |
DOI: | 10.1002/sim.5802 |