| Re: Weighting across surveys when only including youth in analysis [message #13569 is a reply to message #13565] |
Mon, 20 November 2017 23:03   |
Reduced-For(u)m
Messages: 292
Registered: March 2013
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Senior Member |
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I think I answered some of these in a PM, but maybe you didn't get it.
1. The nonexistent population problem comes in the second step when you have to decide how to weight the regression for how the wealth quintile affects family planning needs met...are you doing that separately for each survey? If not, that is where the question of population weighting comes in.
2. What does "level of wealth quintile" mean? Level of what? The underlying wealth index? That is not comparable across countries.
3. For clustering on country, generate a "country" variable, and replace "PSU" with "country" in your command line. Or, drop that part, and in your regression include " , cluster(country)". If you mean for the first part where you are estimating "levels of quintiles" then it doesn't matter at all to have the clustering command since it sounds like you are just plugging those estimates into the RHS of a second regression (note: you'd mess up your standard errors in your second stage regression (on family planning needs) that way by not accounting for the uncertainty in your first step estimates, but the only obvious way to deal with that is to use a two-stage bootstrap..that's another post or you can PM me about it).
4. I'm still worried about comparability of "wealth quintile" across time and space. You can't really compare it across countries...but that is beyond the scope of these questions.
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