/* This sas program will produce the estimates in Example 4.1
    of Sampling:  Design and Analysis by Sharon L. Lohr,
    using Version 7 of SAS */

 /* Author:  S. Lohr, 3/99.  Copyright (c) Sharon L. Lohr, 1999*/

options ls=78 ps=35;
 
 /* Create dataset containing strata totals */
data strattot;
   input region $  _total_;
   cards;
NE 220
NC 1054
S  1382
W  422
;

proc print data=strattot;

data agstrat;
   infile '~atsll/public/stp535/bookdata/agstrat.dat' delimiter=',' firstobs =2;
   input county $ state $ acres92 acres87 acres82 farms92
                          farms87 farms82 largef92 largef87
                          largef82 smallf92 smallf87 smallf82 
                          region $ rn weight;
   if acres92 < 200000 then lt200k = 1;
      else lt200k = 0; /*  counties with fewer than 200000 acres in farms */
   if acres92 = -99 then acres92 =  . ;  /* check for missing values */
   if acres92 = -99 then lt200k =  . ;  

proc sort data=agstrat;
  by region;
proc means data=agstrat mean sum std;
  by region;
  var acres92 weight;
proc means data=agstrat mean sum std;
  var acres92 weight;

/*  Note that without the weight variable this just does the SRS mean 
    SAS simply assigns every observation a weight of 1 */

proc surveymeans data=agstrat total = strattot nobs mean sum; 
   strata region /list;
   var acres92 lt200k;

/*  Here's the correct way to do the analysis */

proc surveymeans data=agstrat total = strattot nobs mean sum; 
   stratum region /list;
   var acres92 lt200k;
   weight weight;
   ods output Statistics=myout;

proc print data=myout;