* USED FOR LOGIT MODEL;
* Hscore = hardcode score;
* Score = score generated internally by SAS;
*First we read in a test data set for you;
data mydata;
 input Y VAR1 VAR2 VAR3;
cards;
1	10	33	4
0	20	21	3
1	30	59	2
1	20	76	1
0	30	24	3
0	20	22	2
1	10	28	2
1	10	49	2
0	30	76	2
1	20	59	2
0	30	45	5
0	30	21	4
0	30	49	2
0	10	23	4
1	10	55	2
0	20	29	3
1	10	49	2
0	20	45	5
0	20	24	3
0	10	30	3
0	10	24	5
1	10	59	2
0	30	31	2
0	20	33	4
0	30	22	3
0	30	29	3
0	10	30	3
0	20	28	3
1	30	59	2
0	30	56	2
1	30	77	1
1	20	97	2
0	20	23	4
0	30	25	4
0	30	23	4
0	30	88	1
0	30	49	2
1	30	76	1
1	20	67	1
1	10	55	2
0	20	26	2
1	20	49	2
1	20	68	1
0	30	45	2
1	20	68	1
0	20	32	5
1	30	22	1
1	30	55	2
1	20	66	1
0	20	29	3
;

*Next we estimate a simple logit model;
proc logistic data=mydata outest=trythis descending;
 model y = var1 var2 var3 / selection=stepwise;
run;

%macro hardcode(myestimates,dev_out,val_out);
OPTIONS NOTES SOURCE SOURCE2 MPRINT MLOGIC MERROR SYMBOLGEN;

data coeff (keep=myvar coef);
length myvar $32;
set &myestimates end=last;
where _type_='PARMS';
file 'c:\vars_1x3r5.txt';
put '%macro sel_var;';
* ---------------------------------------;
* This rearranges the coefficients from the regression in an easier format to output;
* Very handy little routine;
array myarray{*} _numeric_;
length myvar $32;
do j = 1 to dim(myarray);
  if (myarray{j} ^= .) then
  do;
     call vname (myarray{j}, myvar);
     coef=      (myarray{j});
     if not(myvar in ("_LNLIKE_","_RMSE_")) then
     do;
        if myvar ^="INTERCEPT" then
        do;
            put myvar;output;
        end;
     end;
  end;
end;
if last then put '%mend sel_var;';
* ---------------------------------------;

data coeff;
set coeff end=last;
if last then call symput ('nvars',_n_); /* Now we have number of parameters in a macro var */
run;

* Write out hardcode in a macro so you can bring it back in and score the dataset;
data coeff ;
set coeff end=last;

file 'c:\hardcode_xc8f4.txt';
if _n_=1 then do;
 put '%macro myhardcode;';
 put 'hscore = ';
 put  '    ' coef ' + ';
end;
if _n_>1 and _n_ <&nvars then put '     ' myvar ' * ' coef ' + ';

if last then do;
 put '     ' myvar ' * ' coef';';
*Now this turns it into the logistic probability rather than log odds;
 put "hscore = 1  /(1+exp(-(hscore)));";
 put '%mend myhardcode;';
end;
run;

*Scoring dataset with SAS code for Logit model;
data mydata_scored;
 set mydata;
%include 'c:\hardcode_xc8f4.txt';
%myhardcode;
Title Dataset is Scored with Logit Model;
proc print data=mydata_scored (obs=10);
run;
%mend hardcode;

%hardcode(trythis,mydata,mydata);