Modeling Gene-Environment Interactions With Quasi-Natural Experiments

Lauren Schmitz, Dalton Conley

Research output: Contribution to journalArticlepeer-review

19 Scopus citations


This 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.

Original languageEnglish (US)
Pages (from-to)10-21
Number of pages12
JournalJournal of Personality
Issue number1
StatePublished - Feb 1 2017
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Social Psychology


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