Table 1. R² values for height (without refitting).

For sequential LR, lasso and relaxed lasso, the chosen model is based on maximum R² on the validation set. Model (3) to (9) each includes Model (2) plus their own specification as stated in the Form column. The elastic-net picks α = 0.9 based on the validation performance.

Model	Form	$R_{\text{train}}^2$	$R_{\text{val}}^2$	$R_{\text{test}}^2$	Size
(1)	Age + Sex	0.5300	0.5260	0.5288	2
(2)	Age + Sex + 10 PCs	0.5344	0.5304	0.5336	12
(3)	Strong Single SNP	0.5364	0.5323	0.5355	13
(4)	10K Combined	0.5482	0.5408	0.5444	10,012
(5)	100K Combined	0.5833	0.5515	0.5551	100,012
(6)	Sequential LR	0.7416	0.6596	0.6601	17,012
(7)	Lasso	0.8304	0.6992	0.6999	47,673
(8)	Relaxed Lasso	0.7789	0.6718	0.6727	13,395
(9)	Elastic Net	0.8282	0.6991	0.6998	48,268