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From   "Levinson, Arnold" <[email protected]>
To   "'Statalist'" <[email protected]>
Date   Tue, 30 Jun 2009 13:50:47 -0600

Steve,
Sorry for overlooking the obvious. Here are the commands and output. (I note as usual the wonderful output efficiency of Stata over the others.)
arnold
_____________________
*Stata*
svyset skulid [pw=w2f2f3], strata(strat) fpc(fpc) || classid

      pweight: w2f2f3
          VCE: linearized
     Strata 1: strat
         SU 1: skulid
        FPC 1: fpc
     Strata 2: <one>
         SU 2: classid
        FPC 2: <zero>

. svy, subpop(if year==2008 & skulid==80001): mean smkskul 
(running mean on estimation sample)

Survey: Mean estimation

Number of strata =       1          Number of obs    =     131
Number of PSUs   =       9          Population size  = 783.698
                                    Subpop. no. obs  =      16
                                    Subpop. size     = 120.542
                                    Design df        =       8

--------------------------------------------------------------
             |             Linearized
             |       Mean   Std. Err.     [95% Conf. Interval]
-------------+------------------------------------------------
     smkskul |   .5806258    .014649      .5468452    .6144064
--------------------------------------------------------------
Note: 45 strata omitted because they contain no subpopulation members

___________________
SAS:
PROC SURVEYMEANS DATA = ytabstest RATE = FPC;
	VAR SMKSKUL;
	STRATA STRAT;
	CLUSTER SKULID CLASSID;
	WEIGHT SKULWT;
	DOMAIN skulstrat;
RUN;

                                         The SAS System         08:13 Tuesday, June 30, 2009 315

                                   The SURVEYMEANS Procedure

                                          Data Summary
                              Number of Strata                  27
                              Number of Clusters              1282
                              Number of Observations         21212
                              Sum of Weights                 98864

                                           Statistics
                                          Std Error
Variable    Label     N       Mean         of Mean       95% CL for Mean
????????????????????????????????????????????????????????????????????????????  SMKSKUL     SMKSKUL   1706   0.488438      0.015833    0.45735470 0.51952078
????????????????????????????????????????????????????????????????????????????

                                   Domain Analysis: skulstrat

                                           Std Error
skulstrat Variable Label   N     Mean       of Mean      95% CL for Mean
 ????????????????????????????????????????????????????????????????????????????         0  SMKSKUL   SMKSKUL    1690    0.487015    0.016001  0.45560287 0.51842627
1  SMKSKUL   SMKSKUL      16    0.580626    0.104178  0.37624423 0.78500743
 ????????????????????????????????????????????????????????????????????????????

                                         The SAS System         08:13 Tuesday, June 30, 2009 316


PROC DESCRIPT DATA = ytabstest DESIGN = WOR;
	NEST STRAT SKULID CLASSID / MISSUNIT;
	TOTCNT TOTSAMP _MINUS1_ _MINUS1_;
	VAR SMKSKUL;
	CLASS SMKSKUL;
	WEIGHT SKULWT;
	SUBPOPN skulstrat = 1;
RUN;

                                  S U D A A N
            Software for the Statistical Analysis of Correlated Data
           Copyright      Research Triangle Institute     August 2008
                                 Release 10.0


DESIGN SUMMARY: Variances will be computed using the Taylor Linearization Method, Assuming a
Without Replacement (WOR) Design
    Sample Weight: SKULWT
    Stage 1 Stratification Variable: STRAT
    Stage 1 Population Count Variable: TOTSAMP
    Stage 2 NEST Variable: SKULID (stage type is data dependent)
    Stage 2 Population Count Variable: _MINUS1_
    Stage 3 With Replacement Sampling Variable: CLASSID
    Stage 3 Population Count Variable: _MINUS1_


Number of observations read    :  20434    Weighted count :    97843
Observations in subpopulation  :    226    Weighted count :     1650
Denominator degrees of freedom :    128
Date: 06-30-2009                             SUDAAN                                  Page:  1
Time: 13:38:12                                                                       Table: 1

Frequencies and Values for CLASS Variables
by: SMKSKUL.

----------------------------------
SMKSKUL         Frequency    Value
----------------------------------
Ordered
  Position:
  1                     6        0
Ordered
  Position:
  2                    10        1
----------------------------------


Date: 06-30-2009                             SUDAAN                                 Page:   2
Time: 13:38:12                                                                      Table: 1

Variance Estimation Method: Taylor Series (WOR)
For Subpopulation: SKULSTRAT = 1
by: Variable, SUDAAN Reserved Variable One.

--------------------------------------------------------------------
|                 |                  | SUDAAN Reserved Variable    |
| Variable        |                  | One                         |
|                 |                  |-----------------------------|
|                 |                  | Total        | 1            |
--------------------------------------------------------------------
|                 |                  |              |              |
| SMKSKUL         | Sample Size      |           16 |           16 |
|                 | Weighted Size    |       120.54 |       120.54 |
|                 | Total            |        69.99 |        69.99 |
|                 | Lower 95% Limit  |              |              |
|                 |  Total           |       -39.85 |       -39.85 |
|                 | Upper 95% Limit  |              |              |
|                 |  Total           |       179.83 |       179.83 |
|                 | Mean             |      0.58063 |      0.58063 |
|                 | SE Mean          |         0.09 |         0.09 |
|                 | Lower 95% Limit  |              |              |
|                 |  Mean            |      0.39690 |      0.39690 |
|                 | Upper 95% Limit  |              |              |
|                 |  Mean            |      0.76435 |      0.76435 |
--------------------------------------------------------------------

On Tue, Jun 30, 2009 at 1:52 PM, <[email protected]> wrote:
> ==
> Arnold,
>
> We cannot judge the cause of the discrepancy since you do not show the 
> Stata -svyset- output, nor the Stata
> estimation commands and output, nor the equivalent SAS commands and
> output.  Please do so.  If there are so many variables as to make
> scanning the output difficult, please run the commands with as few
> variables as needed to demonstrate the issue. Best would be to use one
> of the downloadable example data sets from the Stata survey manual.
>
> -Steve
>
>
> On Tue, Jun 30, 2009 at 12:41 PM, Levinson,
> Arnold<[email protected]> wrote:
>> Survey analysis experts:
>> I have data from a stratified two-stage school survey. The first stage sampled schools within strata, the second sampled classrooms within selected schools.
>>
>> When estimating variables of interest at the school level, I get hugely different variance estimates running Stata vs. SAS or SUDAAN. Stata's estimates are generally a lot smaller than SAS's or SUDAAN's, and the latter to are similar or identical to each other.
>>
>> My Stata svyset statement is:
>>
>> svyset skulid [pw=skulwt], strata(strat) fpc(fpc) || classid
>>
>> My SAS/SUDAAN design statements are the equivalent.
>>
> Steven Samuels
> [email protected]
> 18 Cantine's Island
> Saugerties NY 12477
> USA
> 845-246-0774
>




Arnold H. Levinson, PhD
Assistant Professor of Community and Behavioral Health
Colorado School of Public Health
Director, Tobacco & Amendment 35 Program Evaluation Group (TPEG, APEG)
13001 E. 17th Place, Mail Stop F542
P.O. Box 6508, Aurora CO 80045
[email protected]
voice: 303-724-3541
fax:    303-724-3544





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