/* Bootstrap resampling and logistic regression */
data mydata;
 input BAD VAR1 VAR2 VAR3 GOOD;
cards;
1	20	97	2	0
1	20	97	2	0
1	20	97	2	0
1	20	76	1	0
0	30	88	1	1
0	30	88	1	1
0	30	88	1	1
1	10	59	2	0
1	10	59	2	0
1	10	59	2	0
1	10	55	2	0
1	10	55	2	0
1	10	55	2	0
1	10	55	2	0
1	10	55	2	0
1	10	55	2	0
1	20	68	1	0
1	20	68	1	0
1	20	68	1	0
1	20	68	1	0
1	20	68	1	0
1	20	68	1	0
1	20	67	1	0
1	20	67	1	0
1	20	67	1	0
1	20	66	1	0
1	20	66	1	0
1	20	66	1	0
1	30	77	1	0
1	30	77	1	0
1	30	77	1	0
0	30	76	2	1
1	30	76	1	0
1	30	76	1	0
1	30	76	1	0
1	10	49	2	0
1	10	49	2	0
1	10	49	2	0
1	10	49	2	0
1	20	59	2	0
1	20	49	2	0
1	20	49	2	0
1	20	49	2	0
1	10	33	4	0
1	30	59	2	0
1	30	59	2	0
1	30	59	2	0
1	30	59	2	0
0	20	45	5	1
0	20	45	5	1
0	20	45	5	1
0	10	30	3	1
0	10	30	3	1
0	10	30	3	1
0	10	30	3	1
0	10	30	3	1
0	10	30	3	1
0	30	56	2	1
0	30	56	2	1
0	30	56	2	1
1	30	55	2	0
1	30	55	2	0
1	30	55	2	0
1	10	28	2	0
0	10	24	5	1
0	10	24	5	1
0	10	24	5	1
0	10	23	4	1
0	30	49	2	1
0	30	49	2	1
0	30	49	2	1
0	30	49	2	1
0	20	33	4	1
0	20	33	4	1
0	20	33	4	1
0	20	32	5	1
0	20	32	5	1
0	20	32	5	1
0	30	45	5	1
0	30	45	2	1
0	30	45	2	1
0	30	45	2	1
0	20	29	3	1
0	20	29	3	1
0	20	29	3	1
0	20	29	3	1
0	20	29	3	1
0	20	29	3	1
0	20	28	3	1
0	20	28	3	1
0	20	28	3	1
0	20	26	2	1
0	20	26	2	1
0	20	26	2	1
0	20	24	3	1
0	20	24	3	1
0	20	24	3	1
0	20	23	4	1
0	20	23	4	1
0	20	23	4	1
0	20	22	2	1
0	20	21	3	1
0	30	31	2	1
0	30	31	2	1
0	30	31	2	1
0	30	29	3	1
0	30	29	3	1
0	30	29	3	1
0	30	25	4	1
0	30	25	4	1
0	30	25	4	1
0	30	24	3	1
0	30	23	4	1
0	30	23	4	1
0	30	23	4	1
0	30	22	3	1
1	30	22	1	0
0	30	22	3	1
1	30	22	1	0
0	30	22	3	1
1	30	22	1	0
0	30	21	4	1
;

/* THIS PROGRAM WILL CREATE A BOOTSTRAPING DATASET AND RUN A LOGISTIC REGRESSION
EACH TIME A DATASET IS CREATED. THE TABLE 'MEANS_ALL' CREATE THE MEANS OF EACH
DATASET SINCE EACH DATASET ISN'T SAVED TO A TABLE. THE TABLE 'PARMS' IS CREATED
TO HOUSE THE RESULTS OF EACH LOGISTIC REGRESSION. THE PURPOSE OF THIS EXERCISE
IS TO COMPUTE A MEASURE OF ACCURACY ON YOU ORIGINAL DATASET FROM A BOOTSTRAPPING
PROCESS.  
*/

%macro boot(DATASET,NUMBER);

%do i=1 %to &NUMBER;
 data bootstrap; /* next statement selects new observation wo replacement*/
 my_obs_with_replacement=int(ranuni(64387+&i)*totobs)+1;
 set &DATASET nobs=totobs point=my_obs_with_replacement ;
 m+1; 
 if m>totobs then stop;/* needed to keep selection process from going whacky */
 run;
 %if i=1 %then %do;
   proc means noprint;
   output out=means_all;
   run;
   data means_all;
   retain iter;
    set means_all;
	iter=&i;
   run;
 %end;
  %if i>1 %then %do;
   proc means noprint;
   output out=mymeans;
   run;
   data mymeans;
   retain iter;
    set mymeans;
	iter=&i;
   run;
 %end;
 proc logistic data=bootstrap descending NOPRINT outest=mycoeff;
 model bad=var1 var2 var3;
run;
proc append base=parms data=mycoeff;
proc append base=means_all data=mymeans;
run;
%end;
%mend;

%boot(MYDATA, 10);