Re: Weighting the KR for multiple countries [message #363 is a reply to message #362] |
Tue, 23 April 2013 17:15 ![Go to previous message Go to previous message](/theme/default/images/up.png) ![Go to next message Go to previous message](/theme/default/images/down.png) |
Reduced-For(u)m
Messages: 292 Registered: March 2013
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Senior Member |
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I am literally working on this right now, but it is a pretty tough question.
So you append 5 surveys together. What do you want the thing you are estimating to represent? An average of all the people that live in those five countries? An average that thinks of a country as an individual? An average that represents the people sampled in the DHS?
My guess is that intuitively you want the first one. So here is how I've been thinking of it, but I would be very happy if someone pointed out why it was wrong. It's based off the attached note (and modified from it) which was originally posted here:
http://userforum.measuredhs.com/index.php?t=tree&th=54&a mp;goto=82&#msg_82
gen preweight = (v005/1000000)
Now go get population estimates of each country, merge them as "countrypop"
egen countryn = count(Y), by(country)
*for whatever Y is, your outcome
*your weights, I think, should sum to countryn ... that is something mentioned on this board somewhere, but you can check how close that is once you lose some observations due to missing covariates or whatever. You may need another level where you scale the weights to sum to the number of observations.
gen newweight = preweight*(countrypop/countryn)
and now you can set "newweight" as your weight. This should correspond to a "population average of your five countries".
Note, though, the relative size of your countries may basically dominate any across-country differences. I'd do all the regressions/tabulations separately by country too, just so you know.
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