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st: RE: -xtmixed- and multilevel data [Was: Grouping income variables- RECODE COMMAND]


From   <S.Jenkins@lse.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: -xtmixed- and multilevel data [Was: Grouping income variables- RECODE COMMAND]
Date   Thu, 6 Feb 2014 09:32:14 +0000

"Antonio Rodriguez Andres" <Antonio.Andres@emu.edu.tr>:

You are indeed stuck with 23 countries. The cited papers make 2 suggestions that may be relevant to you:

(1) consider whether you are really interested in getting good estimates of the effects of the individual-level predictors, or whether the country effects are integral to your research project. If the former, then you can exploit the large number of persons per country. And there are several modelling approaches at your disposal, including FE or separate regressions for each country.

(2) If country effects are integral, consider whether Bayesian approaches are feasible in your case: there is some Monte Carlo evidence that the estimates of country effects derived using these perform better in the small number of countries case. See the references cited in the paper. As a Stata user, you might combine, say, -runmlwin- (on SSC) with MLwiN. Or similar wrappers that call WinBugs.

Good luck
Stephen

------------------------------

Date: Wed, 5 Feb 2014 13:30:48 +0200
From: "Antonio Rodriguez Andres" <Antonio.Andres@emu.edu.tr>
Subject: st: RE: -xtmixed- and multilevel data [Was: Grouping income variables- RECODE COMMAND]

Dear Stephen,

Your feedback is much appreciated. Based on your research paper, the results
are no longer valid with 23 countries. I am stacked with this issue and how
to proceed. Maybe a good starting point is to replicate your table 3. My
dependent variable is the depression score and the key variable of interest
is having children in home and see how its effect differs across gender.


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