Rectangularizing Hierarchical Data

This program illustrates how to read a hierarchical file and combine all levels of information on a single record. Examples of hierarchical files are census data with housing and person records or fertility data with mother and pregnancy records.

For some purposes, users may find the PSC data utility,extract, a more efficient way to rectangularize data, particularly census and CPS files. For information on this option see the documentation for extract.

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filename pums90  pipe
 'zcat /usr/data/public/us/government/pums/1990/1-1000/1990.Z';
filename out1 '1990m.dat';
/* INPUT data */
data a;
   retain state msapmsa;
   infile pums90;
   input @1 type $1. @;
   if type='H' then do;
      input state $11-12  msapmsa $20-23;
      return;
      end;
   else do;
      input sex 11 race 12-14 age 15-16 marital 17 pwgt1 18-21 
            rpob 29-30 yearsch 51-52 rlabor 91 rearning 127-132;
      if (race ne 2) or age "<" 25 or age ">" 64 or sex=1 then delete;
      else do;
        file out1;
        put state $1-2 msapmsa $4-7 age 9-10 marital 12
            pwgt1 14-17 rpob 19-20 yearsch 22-23 rlabor 25 rearning 27-32
            rage 34 rmarital 36 rrpob 38 ryearsch 40 rrlabor 42;
        output;
      end;
   end;	
run;

***************************************************************************

Additional Notes

In a hierarchical file there can be any number of lower level records following the higher level record.

The following is an example of a census file. The record type (housing (H) or person (P)) is in the first column. A household ID is in the next three columns:

H001040506
P424345299992343
P535098321395832
P341132209212245
H002000394
P334902145394456
H003309387
H004233245
P224879062312789
P334293876109824
P344218970098678
P334123449900723

The number of persons in each household is as follows:

Household ID         Household Size
   001                       3
   002                       1
   003                    empty (0)
   004                       4

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