Table 5.

Within-Network Optimality Regression Analyses: Salience Network.

		β	Std. Err.	t	p	pcorrected†
Efficiency Factor
Overall model: F(6,840) = 1.44, p = 0.196
	PCL-R	−0.007	0.037	−0.20	0.840	1.000
	SUD	−0.024	0.037	−0.63	0.526	1.000
	Age	0.086	0.036	2.35	0.019	0.057
	Race	0.009	0.038	0.23	0.819	1.000
	IQ	−0.046	0.039	−1.20	0.232	0.696
	TBIs	−0.027	0.037	−0.71	0.476	1.000
	Constant	0.010	0.036	0.29	0.774	1.000
Vulnerability Factor
Overall model: F(6,840) = 0.68, p = 0.666
	PCL-R	−0.002	0.034	−0.05	0.963	1.000
	SUD	−0.020	0.035	−0.58	0.561	1.000
	Age	−0.011	0.034	−0.33	0.743	1.000
	Race	−0.038	0.036	−1.06	0.289	0.867
	IQ	−0.007	0.036	−0.19	0.846	1.000
	TBIs	0.059	0.035	1.71	0.087	0.261
	Constant	0.025	0.034	0.75	0.451	1.000
Hubness Factor
Overall model: F(6,840) = 0.89, p = 0.499
	PCL-R	0.031	0.038	0.81	0.420	1.000
	SUD	−0.012	0.039	−0.30	0.764	1.000
	Age	0.020	0.038	0.54	0.593	1.000
	Race	−0.016	0.040	−0.39	0.694	1.000
	IQ	−0.028	0.040	−0.71	0.479	1.000
	TBIs	0.076	0.039	1.95	0.051	0.153
	Constant	−0.019	0.038	−0.52	0.606	1.000

^†β-values were corrected for the three comparisons in the salience network within-network optimality analysis.