Modeling Gene-Environment Interactions With Quasi-Natural Experiments

Journal of Personality
Lauren Schmitz, Dalton Conley

Abstract

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.

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Citations

Dec 12, 2017·Genes, Brain, and Behavior·Danielle M DickJinni Su
Oct 4, 2018·Proceedings of the National Academy of Sciences of the United States of America·Silvia H BarcellosPatrick Turley
May 6, 2021·Scientific Reports·Evelina T AkimovaMelinda C Mills

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