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Modeling Gene‐Environment Interactions With Quasi‐Natural Experiments

dc.contributor.authorSchmitz, Lauren
dc.contributor.authorConley, Dalton
dc.date.accessioned2017-02-02T22:01:22Z
dc.date.available2018-04-02T18:03:23Zen
dc.date.issued2017-02
dc.identifier.citationSchmitz, Lauren; Conley, Dalton (2017). "Modeling Gene‐Environment Interactions With Quasi‐Natural Experiments." Journal of Personality 85(1): 10-21.
dc.identifier.issn0022-3506
dc.identifier.issn1467-6494
dc.identifier.urihttps://hdl.handle.net/2027.42/136008
dc.description.abstractThis overview develops new empirical models that can effectively document Gene × Environment (G×E) interactions in observational data. Current G×E studies are often unable to support causal inference because they use endogenous measures of the environment or fail to adequately address the nonrandom distribution of genes across environments, confounding estimates. Comprehensive measures of genetic variation are incorporated into quasi‐natural experimental designs to exploit exogenous environmental shocks or isolate variation in environmental exposure to avoid potential confounders. In addition, we offer insights from population genetics that improve upon extant approaches to address problems from population stratification. Together, these tools offer a powerful way forward for G×E research on the origin and development of social inequality across the life course.
dc.publisherPrinceton University Press
dc.publisherWiley Periodicals, Inc.
dc.titleModeling Gene‐Environment Interactions With Quasi‐Natural Experiments
dc.typeArticleen_US
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelPsychology
dc.subject.hlbtoplevelSocial Sciences
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/136008/1/jopy12227_am.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/136008/2/jopy12227.pdf
dc.identifier.doi10.1111/jopy.12227
dc.identifier.sourceJournal of Personality
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dc.owningcollnameInterdisciplinary and Peer-Reviewed


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