The HPNLMOD Procedure

(View the complete code for this example.)

In Example 82.3 cancer remission is modeled by expressing the maximum likelihood function for a binary distribution as a nonlinear least squares optimization. The following statements show an equivalent formulation of this model that uses PROC HPNLMOD and specifies the binary distribution explicitly:

proc hpnlmod data=remiss corr;
   parms int=-10 a=-2 b=-1 c=6;
   linp = int + a*cell + b*li + c*temp;
   p = probnorm(linp);
   model remiss ~ binary(1-p);
run;

This binary distribution model displays information about the quality of the estimation that is different from the information displayed in the section Least Squares Model. No analysis of variance table is produced for this model; fit statistics that are based on the value of the likelihood function are displayed in Figure 57.3.

Parameter estimates for the binary distribution model that uses the same quantities as are used in the section Least Squares Model are displayed in Figure 57.4.