Esen, Buket Öztürk;
Ehrenstein, Vera;
Petersen, Irene;
Sørensen, Henrik Toft;
Pedersen, Lars;
(2024)
Understanding the impact of non-shared unmeasured confounding on the sibling comparison analysis.
International Journal of Epidemiology
, 53
(1)
, Article dyad179. 10.1093/ije/dyad179.
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Preprint_Esen_BO_Understanding_the_impact_of_nonshared_unmeasured_confounding_on_the_sibling_comparison_analysis.pdf - Accepted Version Access restricted to UCL open access staff until 19 December 2024. Download (1MB) |
Abstract
BACKGROUND: The sibling comparison analysis is used to deal with unmeasured confounding. It has previously been shown that in the presence of non-shared unmeasured confounding, the sibling comparison analysis may introduce substantial bias depending on the sharedness of the unmeasured confounder and the sharedness of the exposure. We aimed to improve the awareness of this challenge of the sibling comparison analysis. METHODS: First, we simulated sibling pairs with an exposure, a confounder and an outcome. We simulated sibling pairs with no effect of the exposure on the outcome and with positive confounding. For varying degrees of sharedness of the confounder and the exposure and for varying prevalence of the exposure, we calculated the sibling comparison odds ratio (OR). Second, we provided measures for sharedness of selected treatments based on Danish health data. RESULTS: The confounded sibling comparison OR was visualized for varying degrees of sharedness of the confounder and the exposure and for varying prevalence of the exposure. The confounded sibling comparison OR was seen to increase with increasing sharedness of the exposure and the confounded sibling comparison OR decreased with an increasing prevalence of exposure. Measures for sharedness of treatments based on Danish health data showed that treatments of chronic diseases have the highest sharedness and treatments of non-chronic diseases have the lowest sharedness. CONCLUSIONS: Researchers should be aware of the challenge regarding non-shared unmeasured confounding in the sibling comparison analysis, before applying the analysis in non-randomized studies. Otherwise, the sibling comparison analysis may lead to substantial bias.
| Type: | Article |
|---|---|
| Title: | Understanding the impact of non-shared unmeasured confounding on the sibling comparison analysis |
| Location: | England |
| DOI: | 10.1093/ije/dyad179 |
| Publisher version: | http://dx.doi.org/10.1093/ije/dyad179 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Bias, non-shared unmeasured confounding, sibling comparison analysis, simulation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health > Primary Care and Population Health |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10188961 |
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