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st: -xtmixed- and multilevel data [Was: Grouping income variables- RECODE COMMAND]
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st: -xtmixed- and multilevel data [Was: Grouping income variables- RECODE COMMAND]
Date
Wed, 5 Feb 2014 10:07:44 +0000
In addition to having issues with how to deal with grouped income data with missing values, I note that Antonio Rodriguez Andres <[email protected]> is using European Social Survey data -- pooling data for 23 countries, with a large number of respondents per country, and then fitting a mixed model.
I suggest that Antonio proceed with caution with this modelling approach. The number of countries is "small" and so country effects (coefficients on country fixed effects or random effect variances) may not be reliably estimated.
For a review of the issues, see:
'Regression analysis of cross-national differences using multi-level data: a cautionary tale', Working Paper 2013-14. Colchester: Institute for Social and Economic Research, University of Essex. https://www.iser.essex.ac.uk/publications/working-papers/iser/2013-14
Related: see also "A Monte Carlo analysis of multilevel binary logit model estimator performance" presented at the 2013 UKSUG: http://www.stata.com/meeting/uk13/abstracts/
Stephen
------------------
Stephen P. Jenkins <[email protected]>
Date: Tue, 4 Feb 2014 14:48:54 +0200
From: "Antonio Rodriguez Andres" <[email protected]>
Subject: RE: st: Grouping income variables- RECODE COMMAND
Dear Maarten
Thank you very much for your feedback. What I did is the following
http://www3.nd.edu/~rwilliam/stats2/l12.pdf
*Create income midpoints
recode hinctnt (1=900) (2=2700) (3=4800) (4=9000) (5=15000) (6=21000) (7=27000) (8= 33000) (9=48000) (10=75000) (11=105000) (12= 175200) , gen(hincome)
replace hincome=. if hinctnt==77 | hinctnt==88 | hinctnt==99
gen lhincome=log(hincome)
**dummy indicator for missing income values
gen xhincome=hincome
replace xhincome= 29304.99 if missing(hincome)
gen md=0
replace md=1 if xhincome! =hincome
xtmixed dprt age age2 gender married separated divorced widowed eduyrs ichldhm md lhincome ihealth iuemp5yr iuemp12m rgdp06[pw=dweight] if md==0 || cntry: gender , mle
But I still got the same message, the md indicator variable is dropped. How can Ä° estimate the model controlling for missing values in income?
Antonio
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