Our measure of a score’s predictive power for a predicted phenotype is the incremental R2 (or incremental pseudo-R2) from adding the score to a regression of the phenotype on controls for sex, birth year, birth-year squared, birth-year cubed, as well as the interactions between sex and the three birth-year variables, and the first ten principal components of the genetic relatedness matrix. We used the bootstrap method with 1,000 iterations to estimate 95% percentile confidence intervals for the incremental R2 estimates. For continuous phenotypes, we estimated ordinary least squares (OLS) regressions; for binary phenotypes (e.g., ever smoker), we estimated probit models; and for censored phenotypes (e.g., equity share, which is nonnegative), we estimated tobit models. For binary and censored phenotypes, we used McFadden’s pseudo-R2 to calculate the incremental pseudo-R2.
