* Remission Example -- source code file remission.sas;

options linesize=70 nodate;
data remission;
      input remiss cell smear infil li blast temp;
      label remiss='Complete Remission';
      datalines;
1   .8   .83  .66  1.9  1.1     .996
1   .9   .36  .32  1.4   .74    .992
0   .8   .88  .7    .8   .176   .982
0  1     .87  .87   .7  1.053   .986
1   .9   .75  .68  1.3   .519   .98
0  1     .65  .65   .6   .519   .982
1   .95  .97  .92  1    1.23    .992
0   .95  .87  .83  1.9  1.354  1.02
0  1     .45  .45   .8   .322   .999
0   .95  .36  .34   .5  0      1.038
0   .85  .39  .33   .7   .279   .988
0   .7   .76  .53  1.2   .146   .982
0   .8   .46  .37   .4   .38   1.006
0   .2   .39  .08   .8   .114   .99
0  1     .9   .9   1.1  1.037   .99
1  1     .84  .84  1.9  2.064  1.02
0   .65  .42  .27   .5   .114  1.014
0  1     .75  .75  1    1.322  1.004
0   .5   .44  .22   .6   .114   .99
1  1     .63  .63  1.1  1.072   .986
0  1     .33  .33   .4   .176  1.01
0   .9   .93  .84   .6  1.591  1.02
1  1     .58  .58  1     .531  1.002
0   .95  .32  .3   1.6   .886   .988
1  1     .6   .6   1.7   .964   .99
1  1     .69  .69   .9   .398   .986
0  1     .73  .73   .7   .398   .986
;

proc print;
   title 'Stepwise Regression on Cancer Remission Data';

proc logistic data=remission descending outest=betas covout;
   model remiss=cell smear infil li blast temp /
      selection=stepwise slentry=0.3 slstay=0.35
                     details
                     lackfit;
   output out=pred p=phat lower=lcl upper=ucl
      predprobs=(individual crossvalidate);

proc print data=betas;
   title2 'Parameter Estimates and Covariance Matrix';

proc print data=pred;
   title2 'Predicted Probabilities and 95% Confidence Limits';

run;
quit;