PT  - JOURNAL ARTICLE
AU  - Connor, Gregory
AU  - Fuerst, Gerard R.
TI  - Linear and partially linear models of behavioral trait variation using admixture regression
AID  - 10.1101/2021.05.14.444173
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.05.14.444173
4099  - http://biorxiv.org/content/early/2021/09/21/2021.05.14.444173.short
4100  - http://biorxiv.org/content/early/2021/09/21/2021.05.14.444173.full
AB  - Admixture regression methodology exploits the natural experiment of random mating between individuals with different ancestral backgrounds to infer the environmental and genetic components to trait variation across racial and ethnic groups. This paper provides a statistical framework for admixture regression based on the linear polygenic index model and applies it to neuropsychological performance data from the Adolescent Brain Cognitive Development (ABCD) database. We develop and apply a new test of the differential impact of multi-racial identities on trait variation, an orthogonalization procedure for added explanatory variables, and a partially linear semiparametric functional form. We find a statistically significant genetic component to neuropsychological performance differences across racial identities, and find some possible evidence of nonlinearity in the link between admixture and neuropsychological performance scores in the ABCD data.Competing Interest StatementThe authors have declared no competing interest.