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. Author manuscript; available in PMC: 2020 Aug 25.
Published in final edited form as: Adult Resid Care J. 1993 Fall;7(2):88–103.

Table 3.

Logistic Regressions Predicting Staying Open (O = closed; 1 = open) (N = 214)

Facility and Neighborhood Characteristics up to ’73 Facility and Neighborhood Characteristics ’73–’83
B p B p
Intercept .01 .966 2.94 .000
Business Orientation .39 .05 .38 .076
At or Above ATD rate 1.11 .004 .83 .05
Disability Residents .66 .002 .53 .027
Licensure 2.16 .000
Age Facility .000 .927 −.000 .736
Poverty ’70 .44 .051 .46 .064
Increase in Poverty ’70–’80 .22 .450
Mixed Land Use .98 .010 1.05 .042
p for model .0000 .0000
% correctly classified 78. 80.
Somer Dyx .61 .77

The SAS algorithm for computing logistic co-efficients predicts the probability of the non-event (here staying closed). To maintain consistency with the bivariate correlation, signs were switched to predict probability of predicting staying open.