The PROBIT Procedure

Recall the previous example of an epidemic study, in which the treat*sex interaction is statistically significant. Suppose you want to know whether such an effect is the same at different levels of the two categorical variables.

The following SAS statements fit a probit model and use the SLICE statement to request analysis of the two-way interaction term treat*sex:

proc probit data=epidemic;
   class treat sex;
   model r/n = dose treat sex treat*sex;
   slice treat*sex / diff;
   effectplot;
run;

Output 81.5.1 displays the test results for the interaction effect. As you can see, the difference between the two treatments is not significant among females.

The DIFF option computes effect differences between groups within the same slice. Results are displayed in Output 81.5.2.

The EFFECTPLOT statement produces a predicted probability plot for dose by the four groups that are formed by the treat*sex interaction. The plot is displayed in Output 81.5.3. The two overlapping curves represent the two treatment groups for females, suggesting no treatment effect. It appears that males tend to respond to the two treatments differently: those on treatment B have a better survival rate, and those on treatment A have a worse chance of survival.

Output 81.5.3: Predicted Probability versus Dose Level by treat*sex