Table 2.

Model fitting results

	ep	−2LL	df	AIC	Δ−2LL	Δdf	P	Comparison model
Bivariate model
1: Cholesky	29	26 072.78	8446	9179.78	–	–	–	–
2: L-COG↔L-SZ	29	26 072.78	8446	9179.78	–	–	–	–
3: Dropping L-SZ→L-COG	28	26 074.57	8447	9179.57	1.79	1	0.18	1 and 2
4: Dropping L-COG→L-SZ	28	26 092.64	8447	9197.64	19.85	1	<0.01	1 and 2
Trivariate model
1: Full	32	29 736.61	9752	10 232.61	–	–	–	–
2: Dropping PRs→L-COG (j)	31	29 759.54	9753	10 253.54	22.94	1	<0.01	1
3: Dropping PRS→L-SZ (i)	31	29 751.26	9753	10 245.26	14.65	1	<0.01	1
4: Dropping L-SZ→L-COG (k′)	31	29 737.85	9753	10 231.85	1.24	1	0.26	1
5: Dropping L-COG→L-SZ (k)	31	29 758.10	9753	10 252.10	21.49	1	<0.01	1

Δ − 2LL = the difference of minus 2 log likelihood between two models; Δdf = the difference of the degrees of freedom; −2LL = minus 2 log likelihood; AIC = Akaike information criterion; ep = estimate parameter; df = degree of freedom; P = P-value, when P-value < 0.05 (P-value < 0.025 for bivariate), the model is significantly worse than the comparison model.

The overall genetic variance to L-SZ is constrained to 0.82.