Use of genetic correlations to examine selection bias.
correlation
covariance
selection bias
Journal
Genetic epidemiology
ISSN: 1098-2272
Titre abrégé: Genet Epidemiol
Pays: United States
ID NLM: 8411723
Informations de publication
Date de publication:
30 Jul 2024
30 Jul 2024
Historique:
revised:
13
07
2024
received:
04
04
2023
accepted:
17
07
2024
medline:
31
7
2024
pubmed:
31
7
2024
entrez:
31
7
2024
Statut:
aheadofprint
Résumé
Observational studies are rarely representative of their target population because there are known and unknown factors that affect an individual's choice to participate (the selection mechanism). Selection can cause bias in a given analysis if the outcome is related to selection (conditional on the other variables in the model). Detecting and adjusting for selection bias in practice typically requires access to data on nonselected individuals. Here, we propose methods to detect selection bias in genetic studies by comparing correlations among genetic variants in the selected sample to those expected under no selection. We examine the use of four hypothesis tests to identify induced associations between genetic variants in the selected sample. We evaluate these approaches in Monte Carlo simulations. Finally, we use these approaches in an applied example using data from the UK Biobank (UKBB). The proposed tests suggested an association between alcohol consumption and selection into UKBB. Hence, UKBB analyses with alcohol consumption as the exposure or outcome may be biased by this selection.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Medical Research Council
ID : MC_UU_00011/1 MC_UU_00011/3
Pays : United Kingdom
Informations de copyright
© 2024 The Author(s). Genetic Epidemiology published by Wiley Periodicals LLC.
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