Open AccessMortality selection in a genetic sample and implications for association studies
Author(s) -
Benjamin W. Domingue,
Daniel W. Belsky,
Amal Harrati,
Dalton Conley,
David R. Weir,
Jason D. Boardman
Publication year - 2017
Publication title -
international journal of epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.406
H-Index - 208
eISSN - 1464-3685
pISSN - 0300-5771
DOI - 10.1093/ije/dyx041
Subject(s) - selection (genetic algorithm) , confounding , selection bias , inverse probability weighting , cohort , demography , population , genetic association , genetic epidemiology , statistics , medicine , biology , genetics , environmental health , computer science , mathematics , genotype , propensity score matching , gene , single nucleotide polymorphism , machine learning , sociology
Mortality selection occurs when a non-random subset of a population of interest has died before data collection and is unobserved in the data. Mortality selection is of general concern in the social and health sciences, but has received little attention in genetic epidemiology. We tested the hypothesis that mortality selection may bias genetic association estimates, using data from the US-based Health and Retirement Study (HRS).
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