| Re: Weighting in multilevel model with pooled data [message #14083 is a reply to message #14072] |
Mon, 12 February 2018 13:01   |
Bridgette-DHS
Messages: 3155
Registered: February 2013
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Senior Member |
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Following is a response from Senior DHS Stata Specialist, Tom Pullum:
I'm sorry that we do not have a solution for the melogit problem--the requirement of sampling weights for each level, i.e. for the selection of clusters within a stratum and the selection of households within a cluster. We hope to develop a "workaround". If any users have suggestions, I hope they will post them.
Yes, you can use a single-level logit regression, with macro-level variables attached to each respondent through the cluster or region or country code but without separate weights for each level, since you don't have them. It will not be optimal but it may be the best one can do. That's my opinion; other researchers may disagree.
Also, yes, you can construct variables from the individual-level data by aggregating within clusters, within regions, or within countries, and attaching those compositional variables to the individual-level data. As you go to the regional and national level you will have a reduction in degrees of freedom that will limit the use of variables at those levels.
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