Hosmer-Lemeshow test of goodness-of-fit can be performed by using the lackfit option after the model statement. This test divides subjects into deciles based on predicted probabilities, then computes a chi-square from observed and expected frequencies. It tests the null hypothesis that there is no difference between the observed and predicted values of the response variable.Therefore, when the test is not significant, as in this example, we can not reject the null hypothesis and say that the model fits the data well. We can also request the generalized R-square measure for the model by using rsquare option after the model statement. SAS gives the likelihood-based pseudo R-square measure and its rescaled measure.

 Categorical Data Analysis Using The SAS System, by M. Stokes, C. Davis and G. Koch offers more details on how the generalized R-square measures that you can request are constructed and how to interpret them.

 proc logistic data = hsb2;

 class prog(ref='1') /param = ref;

model hiwrite(event='1') = female prog read math / rsq lackfit;

run;