| Re: Weights and Strata for Pooled Samples [message #19762 is a reply to message #19761] |
Mon, 10 August 2020 14:57   |
Trevor-DHS
Messages: 789
Registered: January 2013
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Senior Member |
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Unfortunately you can't just merge the datasets together without adjusting the sample weights. The sample weights are relative weights and are normalized separately to the total number of women and total number of men in the sample. For example for Lesotho DHS 2014, 6621 women were interviewed, but only 2931 men (and that includes men age 15-59, not just 15-49). In Appendix A, it states that "In addition, in a subsample of households (every second household), all men age 15-59 who were usual residents of the households or stayed in the households on the night before the interview were eligible for interview". If you used the merged data without adjusting the weights you would be assuming that there were more than twice as many women in Lesotho than men!
Typically this adjustment is made by applying a constant factor to the weights for women and the weights for men. These constant factors are taken by using estimates of the male and female population age 15-49 in Lesotho from some external source, such as the UN's World Population Prospects or from census data, and dividing by the total sample size for women and for men age 15-49 from the survey.
This same issue applies when you pool data from multiple surveys or multiple countries, each of which have their own weights that will need adjusting.
As for the code adjusting the PSU and stata, I don't know melogit, but I cannot think of another solution if you need to include both women and men in the same model. Can you run separate models for women and for men? Otherwise I don't have a better option.
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