*** SAS file generated by sastangle ***;

options nocenter nodate nonumber ls=80 formdlim='';

*** Code chunk number 1 ***;
proc import
   datafile='c:/book/help.csv'
   out=dsprelim
   dbms=dlm;
   delimiter=',';
   getnames=yes;
run;

data ds;
set dsprelim;
   keep id cesd f1a -- f1t i1 i2 female treat;
run;

*** Code chunk number 2 ***;
options ls=70;   /* narrows width to stay in grey box */
ods select attributes;
proc contents data=ds; 
run;
ods select all;

*** Code chunk number 3 ***;
options ls=70;   /* narrows width to stay in grey box */
ods select variablesshort;
proc contents data=ds short; 
run;
ods select all;

*** Code chunk number 4 ***;
proc print data=ds (obs=3) width=minimum;
run;

*** Code chunk number 5 ***;
libname book 'c:/temp';
data book.ds (label = "HELP baseline dataset");
set ds;
run;

*** Code chunk number 6 ***;
proc export data=ds replace
   outfile="c:/temp/ds.xls"
   dbms=excel;
run;

*** Code chunk number 7 ***;
proc print data=ds (obs=10);
   var cesd;
run;

*** Code chunk number 8 ***;
proc print data=ds;
   where cesd gt 56;
   var cesd;
run;

*** Code chunk number 9 ***;
proc sort data=ds out=dss1;
   by cesd;
run;

proc print data=dss1 (obs=4);
   var id cesd i1 treat;
run;

*** Code chunk number 10 ***;
options ls = 70;
proc means data=ds min q1 median q3 max mean std n nmiss;
   var f1g;
run;

*** Code chunk number 11 ***;
data cesd;
set ds;
   /* list of backwards questions */
   array backwards [*] f1d f1h f1l f1p;
   /* for each, subtract the stored value from 3 */
   do i = 1 to dim(backwards);
      backwards[i] = 3 - backwards[i];
   end;
   /* this generates the sum of the non-missing questions */
   newcesd = sum(of f1a -- f1t);
   /* This counts the number of missing values, per person */
   nmisscesd = nmiss(of f1a -- f1t);
   /* this gives the sum, imputing the mean of non-missing */
   imputemeancesd = mean(of f1a -- f1t) * 20;
run;

*** Code chunk number 12 ***;
proc print data=cesd (obs=20);
   where nmisscesd gt 0;
   var cesd newcesd nmisscesd imputemeancesd;
run;

*** Code chunk number 13 ***;
data ds2;
set ds;
   if i1 eq 0 then drinkstat="abstinent";
   if (i1 eq 1 and i2 le 3 and female eq 1) or 
   (((i1 eq 1) or (i1 eq 2)) and i2 le 4 and female eq 0) 
      then drinkstat="moderate";
   if (((i1 gt 1) or (i2 gt 3)) and female eq 1) or
   (((i1 gt 2) or (i2 gt 4)) and female eq 0)
      then drinkstat="highrisk";
   if nmiss(i1,i2,female) ne 0 then drinkstat="";
run;

*** Code chunk number 14 ***;
proc print data=ds2 (firstobs=365 obs=370);
   var i1 i2 female drinkstat;
run;

*** Code chunk number 15 ***;
proc print data=ds2;
   where drinkstat eq "moderate" and female eq 1;
   var i1 i2 female drinkstat;
run;

*** Code chunk number 16 ***;
proc freq data=ds2;
   tables drinkstat;
run;

*** Code chunk number 17 ***;
proc freq data=ds2;
   tables drinkstat*female;
run;

*** Code chunk number 18 ***;
data ds3;
set ds;
   if female eq 1 then gender="Female";
   else if female eq 0 then gender="Male";
run;

proc freq data=ds3;
   tables female gender;
run;

*** Code chunk number 19 ***;
proc sort data=ds;
   by cesd i1;
run;

proc print data=ds (obs=5);
   var id cesd i1;
run;

*** Code chunk number 20 ***;
data females;
set ds;
   where female eq 1;
run;

proc means data=females mean maxdec=1;
  var cesd;
run;

*** Code chunk number 21 ***;
proc sort data=ds;
   by female;
run;

proc means data=ds mean maxdec=2;
   by female;
   var cesd;
run;