| Re: Pooling data & DV weights [message #17877 is a reply to message #17861] |
Mon, 01 July 2019 14:09  |
Bridgette-DHS
Messages: 3214
Registered: February 2013
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Senior Member |
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Following is a response from DHS Research & Data Analysis Director, Tom Pullum:
There have been many postings on pooling and weights. The term "denormalize the weights" means different things to different people, and I avoid the term. My preference would be to give equal weight to each survey. Say the sum of the weights in each of the three surveys is T1, T2, and T3. You can re-scale the weights in survey 1 by multiplying the original weights by (1/T1). Re-scale the weights in survey 2 by multiplying the original weights by (1/T2). Similarly for survey 3. If you are using Stata and pweights you shouldn't have to do anything else. You could then multiply all the weights by 1000000 but that won't change any results that use pweight.
If you don't adjust the weights this way then the results will be pulled to the largest survey, not the largest country. To adjust to the population size, you would have to go through the preceding step and then multiply the weights for country 1 by P1, where P1 is the population (of the relevant type of respondent) in country 1, multiply the weights for country 2 by P2, where P2 is the population (of the relevant type of respondent) in country 2, and similarly for country 3. It may not be easy to determine P1, P2, and P3 at the time of the survey. When doing this, you may find that the results are too dominated by the largest country and hardly depend at all on the smallest country.
Leaving the weight alone and using country as a covariate will only adjust the intercept. It is likely that all of the associations are different across the three countries. I suggest that you try this; I believe you will see that all the results are still sensitive to changing or not changing the weights.
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