COMPUTE WGT=V005/1000000.

EXECUTE .

* Analysis Preparation Wizard.

CSPLAN ANALYSIS

/PLAN FILE='C:\Users\dell\Downloads\BDHS2011.csaplan'

/PLANVARS ANALYSISWEIGHT=WGT

/SRSESTIMATOR TYPE=WR

/PRINT PLAN

/DESIGN STRATA=V023 CLUSTER=V001

/ESTIMATOR TYPE=WR.

May be I need the exact way for obtaining the standard error. If I avoid the sample design and use sampling weight only, I obtain the same estimates as I found using sampple design but the standard error is not now zero. Thus the issue is the design effect for the small sub-population. Is there any way to avoid such computation problem.

If I am working correctly and the results are theoretically reasonable, can you please inform me the exact reasons.

If there is any other technique, please suggest e hw can I solve the problem.

Regards,

Sumonkanti Das ]]>

This is an SPSS question, not a DHS question, and almost no one at DHS uses SPSS. If you were using Stata, the syntax would be much simpler and you could use the "singleunit()" option, which has been described earlier on the forum. I have no idea what you would do in SPSS.

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A standard error is calculated for an estimate, such as the estimated mean value of an indicator. The procedure to calculate a standard error is the same for any subpopulation (unless you use Bayesian methods for nested populations).

Are you trying to match a number in a DHS report? Are you interested in some specific indicator?

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