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Re: st: Advice on multiple imputation in Stata


From   Maarten buis <maartenbuis@yahoo.co.uk>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Advice on multiple imputation in Stata
Date   Wed, 16 Sep 2009 20:07:02 +0000 (GMT)

Basically, -uvis- is repeatedly called by -ice-, so unless you
really know what you are doing and you have a very good reason, 
you should never touch -uvis-. Instead, you should let -ice- do 
that for you. A good place to start are the Stata Journal 
articles by Patrick Royston that introduce this program.

Royston, P. 2004. Multiple imputation of missing values. Stata 
Journal 4(3): 227-241.

Royston, P. 2005. Multiple imputation of missing values: update.
Stata Journal 5(2): 188-201.

Royston, P. 2005. Multiple imputation of missing values: Update 
of ice. Stata Journal 5(4): 527-536. 

Royston, P. 2007. Multiple imputation of missing values: further 
update of ice, with an emphasis on interval censoring. Stata 
Journal 7(4): 445-464.

You can find these articles here:
http://www.stata-journal.com/archives.html

Hope this helps,
Maarten

--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany

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


--- On Wed, 16/9/09, Thomas Klausch <thomas.klausch@gmail.com> wrote:

> From: Thomas Klausch <thomas.klausch@gmail.com>
> Subject: st: Advice on multiple imputation in Stata
> To: statalist@hsphsun2.harvard.edu
> Date: Wednesday, 16 September, 2009, 6:34 PM
> Dear list members,
> 
> I am working with a set of survey data (n is about 1000)
> which
> contains 36 items with missing values (min 0.1% missing, up
> to 16%
> max). The items are surveyed on a seven point scale, so
> they are,
> strictly speaking, on a categorical measurement level.
> 
> I have only a little theoretical knowledge on imputation
> techniques,
> but virtually no practical experience. What I would like to
> do in
> Stata is something like a multiple imputation using EM
> while
> considering the items metric. Or I would like to use some
> logistic /
> probit link function in a mulinomial model to impute
> categorical
> variables directly.
> 
> I have read a bit about -ice- and -uvis-, whith the latter
> I
> understand that I can impute using -mlogit-, the earlier
> using
> "multiple imputation by chained equations", which I do not
> know of.
> 
> Should I use one of these or is there any other good
> procedure? Can
> anybody recommend / advise me on a good imputation
> procedure for my
> case?
> 
> 
> Best regards and thanks for reading
> Thomas
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> 


      


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