SUDAAN FAQ 
How do I analyze survey data with poststratification?

This example is taken from Levy and Lemeshow's Sampling of Populations.
This example uses the dogcats data set.
proc descript data = dogscats filetype=sas design=wor;
  nest _one_;
  totcnt n;
  weight weight;
  subgroup type;
  levels 2;
  var totexp;
  postvar type;
  postwgt 850 450;
run;
Number of observations read    :     50    Weighted count :     1300
Denominator degrees of freedom :     49

Variance Estimation Method: Taylor Series (WOR)
Post-stratified estimates
by: Variable, TYPE.

-----------------------------------------------------------------------------------
|                 |                  |
| Variable        |                  | TYPE
|                 |                  | Total        | 1            | 2            |
-----------------------------------------------------------------------------------
|                 |                  |              |              |              |
| TOTEXP          | Sample Size      |           50 |           32 |           18 |
|                 | Weighted Size    |      1300.00 |       850.00 |       450.00 |
|                 | Total            |     52149.67 |     42379.67 |      9770.00 |
|                 | Mean             |        40.12 |        49.86 |        21.71 |
|                 | SE Mean          |         1.16 |         1.44 |         1.97 |
-----------------------------------------------------------------------------------
This example is taken from Lehtonen and Pahkinen's Practical Methods for Design and Analysis of Complex Surveys.
page 97 Table 3.10  A simple random sample drawn without replacement from the Province'91 population with poststratum weights.
data page97;
  input id str clu wt ue91 lab91 poststr gwt postwt sruv srcvs ;
  fpc = 32;
  cards;
  1 1 1 4 4123 33786 1 .5833 2.333 .25 .43
  2 1 4 4 760 5919 1 .5833 2.333 .25 .43
  3 1 5 4 721 4930 1 .5833 2.333 .25 .43
  4 1 15 4 142 675 2 1.2500 5.0000 .25 .20
  5 1 18 4 187 1448 2 1.2500 5.0000 .25 .20
  6 1 26 4 331 2543 2 1.2500 5.0000 .25 .20
  7 1 30 4 127 1084 2 1.2500 5.0000 .25 .20
  8 1 31 4 219 1330 2 1.2500 5.0000 .25 .20
  ;
run;
poststratified conditional estimates

Note that you cannot get the deff with the postvar/postwgt statements.  The numbers on the postwgt statement must be integers (i.e., whole numbers) and are the population totals.
proc descript data = page97 filetype = sas design = wor totals ;
  weight wt;
  nest _one_;
  totcnt fpc;
  var ue91;
  subgroup poststr;
  levels 2;
  postvar poststr;
  postwgt 7 25;
run;
Number of observations read    :      8    Weighted count :       32
Denominator degrees of freedom :      7
Variance Estimation Method: Taylor Series (WOR)
Post-stratified estimates
by: Variable, POSTSTR.

-----------------------------------------------------------------------------------
|                 |                  |
| Variable        |                  | POSTSTR
|                 |                  | Total        | 1            | 2            |
-----------------------------------------------------------------------------------
|                 |                  |              |              |              |
| UE91            | Sample Size      |            8 |            3 |            5 |
|                 | Weighted Size    |        32.00 |         7.00 |        25.00 |
|                 | Total            |     18106.00 |     13076.00 |      5030.00 |
|                 | SE Total         |      6013.65 |      5966.47 |       751.81 |
|                 | Mean             |       565.81 |      1868.00 |       201.20 |
|                 | SE Mean          |       187.93 |       852.35 |        30.07 |
-----------------------------------------------------------------------------------
poststratified unconditional estimates
This has been skipped for now.

pure design-based estimated under srs
proc descript data = page97 filetype = sas design = wor totals deff;
  weight wt;
  nest _one_;
  totcnt fpc;
  var ue91;
run;
Number of observations read    :      8    Weighted count :       32
Denominator degrees of freedom :      7
Variance Estimation Method: Taylor Series (WOR)
by: Variable, One.

-----------------------------------------------------
|                 |                  |
| Variable        |                  | One
|                 |                  | 1            |
-----------------------------------------------------
|                 |                  |              |
| UE91            | Sample Size      |            8 |
|                 | Weighted Size    |        32.00 |
|                 | Total            |     26440.00 |
|                 | SE Total         |     13282.26 |
|                 | Mean             |       826.25 |
|                 | SE Mean          |       415.07 |
|                 | DEFF Mean #4     |         0.75 |
|                 | DEFF Total #4    |         0.75 |
-----------------------------------------------------

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