| Re: sample weights when using a subsample [message #10886 is a reply to message #10877] |
Wed, 28 September 2016 08:54  |
Bridgette-DHS
Messages: 3043
Registered: February 2013
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Senior Member |
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Following is a response from Senior DHS Stata Specialist, Tom Pullum:
I recommend that you always use the sampling weights, even for a subsample such as you described. The reason for using the weights is that they correct for relative over-sampling and under-sampling of geographically defined strata and they correct for different levels of nonresponse. The weights are intended to produce unbiased estimates of proportions, means, rates, etc. Without using the weights, the estimates will be biased toward areas that were over-sampled or had the highest response rates. Comparisons between the India surveys, for example, to estimate changes, will be meaningless if you do not use weights.
The only exceptions to using weights, so far as I am concerned, would be for checking data quality, checking recodes, and a few other situations where you are just testing a Stata command or program, listing cases, etc.
I recommend using weights for all analyses, including statistical models such as logit regression. I know some people do not use weights, or make other adjustments for clustering and stratification in the sample design, which can affect the standard errors of the estimates (but not the estimates themselves). I would be interested in whether any users of the DHS forum would take that position, and what reasons they would give.
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