Biostatistics

11.4 LOGISTIC REGRESSION 579
Model Summary
Cox & Snell R
Nagelkerke R
Square
Square
.037 .051
Classification Table a
att
Predicted
Percentage
Observed
0 1
Correct
att 0
1
111
58
Overall Percentage
10
5
91.7
7.9
63.0
FIGURE 11.4.5
11.4.2.
Partial SPSS output for the logistic regression analysis of the data in Example
reclassified, with those participating in the rehabilitation program much more poorly classified
than those who did not attend the program. The frequency distribution shows the large
number of ATT ¼ 1 subjects who were misclassified as ATT ¼ 0 based on the model. &
EXAMPLE 11.4.5
Consider the logistic regression model that was constructed from the cardiac rehabilitation
program data in Example 11.4.3.
Figure 11.4.6 shows standard SPSS output for this logistic regression model. In this
figure, we see that both the Cox and Snell and the Nagelkerke pseudo-R 2 values are provided,
and since they are both > 0, the model with the predictors provides more information than
the intercept-only model. One can readily see that only 69% of the data were correctly
reclassified, with the model reclassifying those with onset of excessive alcohol use at a much