Home » Data » Weighting data » Weighting across surveys when only including youth in analysis
| Re: Weighting across surveys when only including youth in analysis [message #13640 is a reply to message #13535] |
Wed, 06 December 2017 17:10   |
cgreenba
Messages: 18
Registered: October 2017
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Hi,
Thank you so much for your response. I apologize for getting back so late, but I am picking the analysis back up and wanted to respond and verify a few things.
1) About the weighting and non-existent population, what I am doing in pooling together the data from the different countries and producing both country-level estimates for the effect on wealth quintile on demand satisfied for family planning as well as a pooled regression analysis with data from all countries. This isn't with the aim for producing a precise estimate for how wealth quintile impact demand satisfied for family planning, but to illustrate in general term what was found when the collection of surveys that were used. I weight each survey by sample size, and not relative size of the population, since I am not attempting to produce some sort of global or regional estimate and instead what to represent what was found across the different surveys included. Does this seem like the right approach?
2) By level of wealth quintile, I simply mean poorest, poorer, middle, richer, and richest quintiles.
3) To cluster the survey data by country, I have used the follow svyset: svyset survey_id, strata(country_id) weight (survey_weight) || psu, strata(strata_id) weight (individual_weight). My goal in using this was to set the survey design so that each survey is weight by in sample size (i.e. survey_weight) and clustered by country (i.e. country_id), which still preserving the psu and strata breakdown for the individual surveys, as well as the individual weights (i.e. v005). So far it seems to be functioning properly, but I would love to verify with others. Does this seem to make sense?
4) As far as the comparability of wealth quintile, while being in the poorest quintile in one country may be extremely different from being in the poorest quintile in another country, using wealth quintile can still tell us something about the effect of being in the poorest or richest quintile of any country on family planning. Isn't this correct? The overall question is more about equity in family planning across countries than have any specific assets or income, which would be harder to compare. I would love to hear any other thoughts on this though.
Thank you so much!
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