Bespoke instrumental variables with nonideal reference populations

Recently, a bespoke instrumental variable method was proposed, which, under certain assumptions, can eliminate bias due to unmeasured confounding when estimating the causal exposure effect among the exposed. This method uses data from both the study population of interest and a reference population in which the exposure is completely absent. In this article, we extend the bespoke instrumental variable method to allow for a nonideal reference population that may include exposed individuals. Such an extension is particularly important in randomized trials with nonadherence, where even individuals in the control arm may have access to the treatment under investigation. We further scrutinize the assumptions underlying the bespoke instrumental method and caution the reader about the potential nonrobustness of the method to these assumptions.

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Publication Details

Journal
American Journal of Epidemiology
Published
2024-08-05
DOI
https://doi.org/10.1093/aje/kwae247
Primary Topic
Statistical Methods and Bayesian Inference
Type
article
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article

Bespoke instrumental variables with nonideal reference populations

Erin E. Gabriel, Arvid Sjölander
2 links
American Journal of Epidemiology
Statistical Methods and Bayesian Inference
article

Bespoke instrumental variables with nonideal reference populations

Erin E. Gabriel, Arvid Sjölander
article en

Abstract

Recently, a bespoke instrumental variable method was proposed, which, under certain assumptions, can eliminate bias due to unmeasured confounding when estimating the causal exposure effect among the exposed. This method uses data from both the study population of interest and a reference population in which the exposure is completely absent. In this article, we extend the bespoke instrumental variable method to allow for a nonideal reference population that may include exposed individuals. Such an extension is particularly important in randomized trials with nonadherence, where even individuals in the control arm may have access to the treatment under investigation. We further scrutinize the assumptions underlying the bespoke instrumental method and caution the reader about the potential nonrobustness of the method to these assumptions.

American Journal of EpidemiologyVol. 194(4)
University of Copenhagen (DK), Karolinska Institutet (SE)
Openalex Percentile: Top 87%
Statistical Methods and Bayesian Inference
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Bespoke instrumental variables with nonideal reference populations — Erin E. Gabriel, Arvid Sjölander · American Journal of Epidemiology (2024) | TGRS Research Map | TGRS