Table 4.

Parameter estimates in the best-fitting IV-CLPM model applied to smoking status and alcohol use.

Parameter	Description	Estimate	SE	Wald’s T	p-Value
Regression paths
bx1	PGS of Smoking (Smk) → Smk at T1	0.146	0.016	8.901	0.0000
bx2	PGS of Smk → Smk at T2	0.014	0.013	1.085	0.2777
by1	PGS of Alcohol (Alc) → Alc at T1	0.169	0.021	8.054	0.0000
by2	PGS of Alc → Alc at T2	0.037	0.018	2.036	0.0418
bx2x1	Smk at T1 → Smk at T2	0.808	0.022	36.461	0.0000
by2x1	Smk at T1 → Alc at T2 (Distal)	0.065	0.027	2.404	0.0162
bx1y1	Alc at T1 → Smk at T1 (Proximal)	0.196	0.094	2.095	0.0362
by2y1	Alc at T1 → Alc at T2	0.662	0.015	44.032	0.0000
(Co)variances
Vpx	Variance of the PGS of Smk	1.000	0.020	49.472	0.0000
Cixiy	Covariance of the PGSs	0.196	0.015	13.441	0.0000
Vpy	Variance of the PGS of Alc	1.000	0.020	49.472	0.0000
Vx1	Residual variance of Smk at T1	0.726	0.040	18.248	0.0000
Cx1y1	Covariance of residuals of Smk and Alc at T1	−0.119	0.158	−0.751	0.4526
Vy1	Residual variance of Alc at T1	1.679	0.040	41.973	0.0000
Vx2	Residual variance of Smk at T2	0.179	0.010	18.803	0.0000
Cx2y2	Covariance of residuals of Smk and Alc at T2	0.047	0.013	3.611	0.0003
Vy2	Residual variance of Alc at T2	0.819	0.025	33.486	0.0000
Covariates
b_smk_age	Age → Smk	0.007	0.001	8.026	0.0000
b_alc_age	Age → Alc	0.009	0.001	8.014	0.0000
b_smk_female	Female sex → Smk	−0.088	0.030	−2.974	0.0029
b_alc_female	Female sex → Alc	−0.812	0.039	−21.041	0.0000
Intercepts
b0_resSmkPRS	Intercept (mean) of the PGS of Smk	0.000	0.014	0.000	1.0000
b0_resAlcPRS	Intercept (mean) of the PGS of Alc	0.000	0.014	0.000	1.0000
b0_smk1	Intercept of Smk at T1	−0.347	0.049	−7.007	0.0000
b0_alc1	Intercept of Alc at T1	3.818	0.062	61.984	0.0000
b0_smk2	Intercept of Smk at T2	−0.442	0.052	−8.466	0.0000
b0_alc2	Intercept of Alc at T1	3.580	0.065	54.752	0.0000

Note. Rows shown in bold indicate estimates of the causal paths between smoking status (latent liability scale of an ordinal variable with levels: never–former–current smoking) and alcohol use (drinks per week).