Table 1.

Results from negative binomial regression models of residential change predicting drinking behavior change (n = 266)

Parameter	df	Estimate	SE	IRR	[Wald 95% confidence limits]	Wald χ2
Model A. Number of days drinking in a typical week post-closure
Intercept	1	0.306	0.115	1.358	[1.085, 1.699]		7.12**
Male	1	0.012	0.042	1.012	[0.932, 1.100]		0.09
Under 21	1	0.061	0.058	1.063	[0.949, 1.191]		1.11
Stay with peers	1	0.380	0.088	1.462	[1.229, 1.738]		18.49***
Stay with parents	1	0.512	0.136	1.669	[1.279, 2.177]		14.24***
Pre-close daysa	1	0.207	0.026	1.230	[1.170, 1.294]		65.57***
Dispersion	1	0.109	0.043	1.115	[1.052, 1.267]
Model B. Total number of drinks in a typical week post-closure
Intercept	1	1.228	0.151	3.416	[2.541, 4.592]		66.24***
Male	1	0.059	0.064	1.061	[0.936, 1.202]		0.86
Under 21	1	0.077	0.088	1.080	[0.910, 1.282]		0.77
Stay with peers	1	0.531	0.135	1.700	[1.305, 2.216]		15.42***
Stay with parents	1	0.617	0.206	1.854	[1.238, 2.777]		8.97**
Pre-close drinksb	1	0.057	0.007	1.058	[1.043, 1.074]		59.96***
Dispersion	1	0.881	0.093	2.414	[2.049, 2.953]
Model C. Maximum number of drinks in a typical week post-closure
Intercept	1	0.312	0.121	1.366	[1.078, 1.730]		6.68**
Male	1	0.063	0.046	1.065	[0.974, 1.165]		1.90
Under 21	1	0.007	0.064	1.007	[0.889, 1.141]		0.01
Stay with peers	1	0.399	0.097	1.490	[1.231, 1.804]		16.79***
Stay with parents	1	0.385	0.150	1.469	[1.095, 1.972]		6.58*
Pre-close maxc	1	0.126	0.014	1.134	[1.103, 1.167]		77.56***
Dispersion	1	0.201	0.049	1.222	[1.132, 1.382]

Notes:^a: Pre-close days = number of days drinking in a typical week pre-closure;

^bpre-close drinks = total number of drinks in a typical week pre-closure;

^cpre-close max = maximum number of drinks per day in typical week pre-closure; IRR = incidence rate ratio.

^*p < .05;

^**p < .01;

^***p < .001.