Table 1.

Bias and RMSE of estimating marginal correlations Σ among three traits

		Bias			RMSE
		${\Sigma }_{12}$	${\Sigma }_{13}$	${\Sigma }_{23}$	${\Sigma }_{12}$	${\Sigma }_{13}$	${\Sigma }_{23}$
$h^2=0.1$	${\widehat{\Sigma }}^s$	0.002	–0.027	0.018	0.012	0.030	0.022
	${\widehat{\Sigma }}^r$	–0.002	0.000001	–0.0003	0.011	0.016	0.014
$h^2=0.3$	${\widehat{\Sigma }}^s$	0.009	–0.058	0.039	0.017	0.062	0.044
	${\widehat{\Sigma }}^r$	–0.001	–0.004	0.003	0.014	0.020	0.018
$h^2=0.5$	${\widehat{\Sigma }}^s$	0.010	–0.061	0.043	0.022	0.068	0.049
	${\widehat{\Sigma }}^r$	–0.0005	–0.008	0.006	0.019	0.028	0.024

Note: h² is the overall heritability; $\Sigma =h^2{\Sigma }_g+(1-h^2){\Sigma }_e$. ${\widehat{\Sigma }}^s$ is the sample correlation-based estimate, and ${\widehat{\Sigma }}^r$ is the LD score regression-based estimate.