******************************************************************/

options ls=80 ps=59 nodate; run;

/******************************************************************

  The data look like (first 10 records)

     1 1 33 1 0
     2 0 32 0 0
     3 1 37 0 1
     4 0 36 0 0
     5 1 50 1 1
     6 1 40 0 0
     7 0 35 0 0
     8 1 33 0 0
     9 1 33 0 0
     10 0 31 0 0
          .
          .
          .

  column 1      subject id
  column 2      oral contraceptive indicator (0=no,1=yes)
  column 3      age (years)
  column 4      smoking indicator (0=no,1=yes)
  column 5      binary response -- whether MI has been suffered
                (0=no,1=yes)

******************************************************************/

data mi; infile 'infarc.dat';
  input id oral age smoke mi;
run;

/*****************************************************************

  Fit the logistic regression model using PROC GENMOD.
  We do not use a CLASS statement here, as the covariates are
  either continuous (AGE) or already in "dummy" form (ORAL, SMOKE).
  The model statement with the LINK=LOGIT option results in the 
  logistic regression model in equation (10.21).  The DIST=BINOMIAL
  specifies the Bernoulli distribution, which is the simplest case
  of a binomial distribution.  

******************************************************************/

proc genmod data=mi;
  model mi = oral age smoke / dist = binomial link = logit;
run;