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 <[email protected]> wrote:
> From: Thomas Klausch <[email protected]>
> Subject: st: Advice on multiple imputation in Stata
> To: [email protected]
> 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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