The impact of coarsening an exposure on partial identifiability in instrumental variable settings

In instrumental variable (IV) settings, such as imperfect randomized trials and observational studies with Mendelian randomization, one may encounter a continuous exposure, the causal effect of which is not of true interest. Instead, scientific interest may lie in a coarsened version of this exposure. Although there is a lengthy literature on the impact of coarsening of an exposure with several works focusing specifically on IV settings, all methods proposed in this literature require parametric assumptions. Instead, just as in the standard IV setting, one can consider partial identification via bounds making no parametric assumptions. This was first pointed out in Alexander Balke's PhD dissertation. We extend and clarify his work and derive novel bounds in several settings, including for a three-level IV, which will most likely be the case in Mendelian randomization. We demonstrate our findings in two real data examples, a randomized trial for peanut allergy in infants and a Mendelian randomization setting investigating the effect of homocysteine on cardiovascular disease.

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Publication Details

Journal
Biostatistics
Published
2024-09-27
DOI
https://doi.org/10.1093/biostatistics/kxae042
Primary Topic
Advanced Causal Inference Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

The impact of coarsening an exposure on partial identifiability in instrumental variable settings

Erin E. Gabriel, Arvid Sjölander, Michael Charles Sachs
Biostatistics
Advanced Causal Inference Techniques
article

The impact of coarsening an exposure on partial identifiability in instrumental variable settings

Erin E. Gabriel, Arvid Sjölander, Michael Charles Sachs
article en

Abstract

In instrumental variable (IV) settings, such as imperfect randomized trials and observational studies with Mendelian randomization, one may encounter a continuous exposure, the causal effect of which is not of true interest. Instead, scientific interest may lie in a coarsened version of this exposure. Although there is a lengthy literature on the impact of coarsening of an exposure with several works focusing specifically on IV settings, all methods proposed in this literature require parametric assumptions. Instead, just as in the standard IV setting, one can consider partial identification via bounds making no parametric assumptions. This was first pointed out in Alexander Balke's PhD dissertation. We extend and clarify his work and derive novel bounds in several settings, including for a three-level IV, which will most likely be the case in Mendelian randomization. We demonstrate our findings in two real data examples, a randomized trial for peanut allergy in infants and a Mendelian randomization setting investigating the effect of homocysteine on cardiovascular disease.

BiostatisticsVol. 26(1)
University of Copenhagen (DK), Karolinska Institutet (SE)
Novo Nordisk
Zero hunger
Openalex Percentile: Top 79%
Advanced Causal Inference Techniques
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