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. 2022 Nov 11;47(4):712–734. doi: 10.1007/s12103-022-09698-1

Table 5.

Logistic Regressions predicting Illegal Online Drug Purchases

	Base					Interaction				Full Model
Variable	B	SE(B)	p	OR		B	SE(B)	p	OR	B	SE(B)	p	OR
Spring 2020*	.03	.18	.856	1.03		-.37	.42	.369	.69	-.03	.20	.870	.97
Fall 2020	-.02	17	.903	.98		-.01	.38	.974	.99	.17	.19	.353	1.19
Fall 2021	.55	.16	.001	1.73		1.02	.34	.003	2.76	.54	.17	.002	1.72
GST	.46	.02	< .001	1.59		.49	.06	< .001	1.63	.42	.03	< .001	1.53
GST#Spring 2020*						.09	.08	.268	1.09
GST#Fall 2020						-.00	.07	.962	1.00
GST#Fall 2021						-.10	.07	.122	.90
Male (binary)										.45	.13	.001	1.57
White (binary)										-.30	.14	.028	.74
Non-Hispanic (binary)										-.03	.17	.853	.97
Income										.27	.04	< .001	1.31
Education										.26	.07	< .001	1.29
Age										-.04	.01	< .001	.96
Constant	-4.21	.16	< .001	.01		-4.32	.28	< .001	.01	-4.36	.33	< .001	.013
Pseudo R²	.18				.19					.25
LR Chi²	493 (n = 4,438)				501(n = 4,438)					619 (n = 4,172)

Notes: *base comparison wave is Fall 2019