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Re: st: Grouping income variables- RECODE COMMAND


From   Maarten Buis <maartenlbuis@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Grouping income variables- RECODE COMMAND
Date   Tue, 4 Feb 2014 17:25:55 +0100

Multiple imputation is in principle very easy, but in practice getting
the right imputation model is a very finicky process. So this is
something where I do not feel comfortable giving you advise without
seeing the data and discussing in detail (face to face) what your
analysis plan is. Your best chance is to find a local expert and meet
her or him (and be prepared to pay, because you will be asking a lot
from her or him).

-- Maarten


On Tue, Feb 4, 2014 at 4:52 PM, Antonio Rodriguez Andres
<Antonio.Andres@emu.edu.tr> wrote:
> Maarten
>
> If the graph is telling that the probability of missingnes is not
> independent of the depression score. Clearly, we need to use imputation.
> I have read here and there are different imputation methods
>
> http://www.stata.com/support/faqs/statistics/clustering-and-mi-impute/
>
>  I try to use strategy 1 but I am not sure about the Stata syntax to ımpute
> the values of household income.
>
> Should I use the strategy 3 ? I am not familiar with these methods. Can you
> give me any clue?
>
> mi set wide
> mi register imputed hinctnt
> mi impute regress hinctnt dprt i.cntry
> mi estimate: xtmixed dprt  age age2 gender married separated divorced
> widowed eduyrs ichldhm ihealth iuemp5yr iuemp12m rgdp06 [pw=dweight]  ||
> cntry: gender, mle
>
> Antonio
>
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Maarten Buis
> Sent: Tuesday, February 04, 2014 4:47 PM
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: Grouping income variables- RECODE COMMAND
>
> On Tue, Feb 4, 2014 at 3:19 PM, Antonio Rodriguez Andres wrote:
>> Thank you for detailed response. One of the reviewers was concerned
>> about the missing values in our income Variable. The variable dprt is
>> the depression score across individuals taking values from 0 to 24.
>> How can I observe that the missingnes Is independent of the depression
>> score?
>
> Say, union in my example is wage in yours and grade in my example is
> depression in yours.
>
> *------------------ begin example ------------------ sysuse nlsw88, clear
> gen byte miss = missing(union)
>
> logit miss grade
> predict pr
>
> logit mis i.grade
> testparm i.grade
>
> collapse (mean) miss pr, by(grade)
>
> twoway line miss pr grade
> *------------------- end example -------------------
> * (For more on examples I sent to the Statalist see:
> * http://www.maartenbuis.nl/example_faq )
>
> Hope this helps,
> Maarten
>
> ---------------------------------
> Maarten L. Buis
> WZB
> Reichpietschufer 50
> 10785 Berlin
> Germany
>
> http://www.maartenbuis.nl
> ---------------------------------
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-- 
---------------------------------
Maarten L. Buis
WZB
Reichpietschufer 50
10785 Berlin
Germany

http://www.maartenbuis.nl
---------------------------------

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