Fifth, the dispersion of the simulated sampling distribution of the PRS effect size, depicted in the violin plots in Figure 2 and Figure 3, vary between models. Most notably, the estimates from the fully corrected simulation model A4 (~PRS+Env+Complete Phenotypic PC) demonstrate lower variance than the estimates from simulation model A1 (~PRS). This suggests that correcting PRS effect size estimates via PCA in this way may increase power to detect small PRS effects by reducing the standard deviation of the sampling distribution (standard error) of the estimate. We note that this finding may be specific to ordinary least squares regression models with a continuous outcome variable.
