Addressing unmeasured confounders in cohort studies : Instrumental variable method for a time-fixed exposure on an outcome trajectory
© 2023 The Authors. Biometrical Journal published by Wiley-VCH GmbH..
Instrumental variable methods, which handle unmeasured confounding by targeting the part of the exposure explained by an exogenous variable not subject to confounding, have gained much interest in observational studies. We consider the very frequent setting of estimating the unconfounded effect of an exposure measured at baseline on the subsequent trajectory of an outcome repeatedly measured over time. We didactically explain how to apply the instrumental variable method in such setting by adapting the two-stage classical methodology with (1) the prediction of the exposure according to the instrumental variable, (2) its inclusion into a mixed model to quantify the exposure association with the subsequent outcome trajectory, and (3) the computation of the estimated total variance. A simulation study illustrates the consequences of unmeasured confounding in classical analyses and the usefulness of the instrumental variable approach. The methodology is then applied to 6224 participants of the 3C cohort to estimate the association of type-2 diabetes with subsequent cognitive trajectory, using 42 genetic polymorphisms as instrumental variables. This contribution shows how to handle endogeneity when interested in repeated outcomes, along with a R implementation. However, it should still be used with caution as it relies on instrumental variable assumptions hardly testable in practice.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:66 |
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| Enthalten in: |
Biometrical journal. Biometrische Zeitschrift - 66(2024), 1 vom: 15. Jan., Seite e2200358 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Le Bourdonnec, Kateline [VerfasserIn] |
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| Links: |
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| Themen: |
Causality |
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| Anmerkungen: |
Date Completed 30.01.2024 Date Revised 30.01.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1002/bimj.202200358 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a © 2023 The Authors. Biometrical Journal published by Wiley-VCH GmbH. | ||
| 520 | |a Instrumental variable methods, which handle unmeasured confounding by targeting the part of the exposure explained by an exogenous variable not subject to confounding, have gained much interest in observational studies. We consider the very frequent setting of estimating the unconfounded effect of an exposure measured at baseline on the subsequent trajectory of an outcome repeatedly measured over time. We didactically explain how to apply the instrumental variable method in such setting by adapting the two-stage classical methodology with (1) the prediction of the exposure according to the instrumental variable, (2) its inclusion into a mixed model to quantify the exposure association with the subsequent outcome trajectory, and (3) the computation of the estimated total variance. A simulation study illustrates the consequences of unmeasured confounding in classical analyses and the usefulness of the instrumental variable approach. The methodology is then applied to 6224 participants of the 3C cohort to estimate the association of type-2 diabetes with subsequent cognitive trajectory, using 42 genetic polymorphisms as instrumental variables. This contribution shows how to handle endogeneity when interested in repeated outcomes, along with a R implementation. However, it should still be used with caution as it relies on instrumental variable assumptions hardly testable in practice | ||
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| 700 | 1 | |a Mura, Thibault |e verfasserin |4 aut | |
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| 700 | 1 | |a Trégouët, David-Alexandre |e verfasserin |4 aut | |
| 700 | 1 | |a Proust-Lima, Cécile |e verfasserin |4 aut | |
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