Generalizing Evidence from Randomized Trials using Inverse Probability of Sampling Weights

Authors

Ashley L. Buchanan, University of Rhode IslandFollow
G. Hudgens
Stephen R. Cole
Katie R. Mollan
Paul E. Sax
Eric S. Daar
Adaora A. Adimora
Joseph J. Eron
Michael J. Mugavero

Document Type

Article

Date of Original Version

2018

Department

Pharmacy Practice

Abstract

Results obtained in randomized trials may not easily generalize to target populations. Whereas in randomized trials the treatment assignment mechanism is known, the sampling mechanism by which individuals are selected to participate in the trial is typically not known and assuming random sampling from the target population is often dubious. We consider an inverse probability of sampling weighted (IPSW) estimator for generalizing trial results to a target population. The IPSW estimator is shown to be consistent and asymptotically normal. A consistent sandwich-type variance estimator is derived and simulation results are presented comparing the IPSW estimator to a previously proposed stratified estimator. The methods are then utilized to generalize results from two randomized trials of HIV treatment to all people living with HIV in the US.

Citation/Publisher Attribution

Buchanan, A. L., Hudgens, M. G., Cole, S. R., Mollan, K. R., Sax, P. E., Daar, E. S., Adimora, A. A., Eron, J. J. and Mugavero, M. J. (2018), Generalizing evidence from randomized trials using inverse probability of sampling weights. J. R. Stat. Soc. A, 181: 1193-1209. doi:10.1111/rssa.12357

Available at: https://doi.org/10.1111/rssa.12357