Table 3.

Results of Hierarchical Linear Modeling Analyses with ROI Response to Reward Predicting Growth in Substance Use (SU) Frequency, for Users

	R NAc to SU Frequency			L NAc to SU Frequency			R vmPFC to SU Frequency			L vmPFC to SU Frequency
Fixed	B	SE	P	B	SE	P	B	SE	p	B	SE	P
Effects
For Intercep:
Intercept	0.64	0.16	<001***	0.66	0.20	.002**	0.67	0.18	<001***	0.69	0.20	.002**
Sex	−0.25	0.24	.32	−0.30	0.27	.27	−0.31	0.25	.22	−0.36	0.31	.25
ROI Resp	0.004	0.01	.72	0.001	0.01	.88	−0.005	0.01	.66	−0.01	.01	.40
Sex X ROI Resp	0.01	0.01	.55	0.01	0.01	.37	0.03	0.01	.02*	0.02	0.01	.11
For Slope: Intercept	−.40	0.29	.18	−.48	0.28	.10	−0.38	0.28	.18	0.41	0.29	.17
Sex	0.18	0.31	.57	0.38	0.25	.15	0.14	0.24	.57	0.22	0.26	.42
ROI Resp	−0.003	0.01	.79	0.005	0.01	.57	−0.001	0.01	.95	0.002	0.01	.82
Sex X	−0.02	.01	.27	−.03	.01	.01*	−.04	.02	.03*	−.03	.01	.01*
ROI Resp For Slope2: Intercept	0.29	0.07	<001***	.28	.07	<001***	0.29	0.07	<001***
Random Effects	Var	SD	P	Var	SD	P	Var	SD	P	Var	SD	P
Intercept	0.32	0.56	<001***	0.32	0.56	.001**	0.26	0.51	.004	0.29	0.54	.002**
Slope	0.44	0.67	<001***	0.39	0.62	<001***	0.37	0.60	<001***	0.39	0.63	<001***
Level-1 Error	0.70	0.83		0.69	0.83		0.70	0.83		0.69	0.83

Note. R = right; L = left; SU = substance use; ROI = region of interest; Resp = response; B = unstandardized regression coefficient; Var = Variance component. This analysis uses n = 41- youth with reward task data who used substances. Uncorrected p values are presented here. FDR-corrected p values for significant main effects or interactions are presented in the text.

^*p < .05

^**p < .01

^***p < .001