Home » Data » Weighting data » Regarding de-normalizing and weighting procedures in Stata
| Re: Regarding de-normalizing and weighting procedures in Stata [message #9564 is a reply to message #9538] |
Mon, 18 April 2016 11:21   |
Bridgette-DHS
Messages: 3230
Registered: February 2013
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Senior Member |
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Following is a response from Senior DHS Stata Specialist, Tom Pullum:
If you multiply all the weights by a constant, you will not alter any of the usual estimates--means, proportion, regression coefficients, etc. I suggest that you try it, using iweight or fweight, and do a comparison.
Moreover, in any operation with pweight, Stata will automatically re-normalize so that the total number of weighted cases equals the total number of unweighted cases. That's why you will get exactly the same means, proportions, regression, coefficients, etc., using pweight=v005 or pweight=v005/1000000. You may think you are de-normalizing v005, but pweight will always re-normalize. Again, try it and compare results.
I would describe the weights you propose as "inflation weights". You would use them to inflate to the total population. You could do this if you want to estimate, for example, the NUMBER of women whose last birth was in a facility, etc. (For this purpose you do need to divide v005 by 1000000.) I would not recommend using inflation weights to inflate to the total population, but that's up to you.
If you are planning to make this adjustment and then pool surveys, you will have to expect that countries with a large population will completely dominate the analysis. The pool of all surveys will be normalized but the weighted subtotals will be in proportions to the population sizes.
I agree with you about not making the adjustments for clustering and stratification, unless you will be using the standard errors. Those adjustments only affect the standard errors, not the estimates.
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