Extending inferences from a cluster randomized trial to a target population
Methodology
2022-03-29 v1
Abstract
We describe methods that extend (generalize or transport) causal inferences from cluster randomized trials to a target population of clusters, under a general nonparametric model that allows for arbitrary within-cluster dependence. We propose doubly robust estimators of potential outcome means in the target population that exploit individual-level data on covariates and outcomes to improve efficiency and are appropriate for use with machine learning methods. We illustrate the methods using a cluster randomized trial of influenza vaccination strategies conducted in 818 nursing homes nested in a cohort of 4,475 trial-eligible Medicare-certified nursing homes.
Cite
@article{arxiv.2203.14761,
title = {Extending inferences from a cluster randomized trial to a target population},
author = {Issa J. Dahabreh and Sarah E. Robertson and Jon A. Steingrimsson and Stefan Gravenstein and Nina Joyce},
journal= {arXiv preprint arXiv:2203.14761},
year = {2022}
}