I don't think it is only you. I guess that
all concerned, StataCorp included, would
agree that there is a lot of interesting,
important stuff in this field not implemented in Stata.
And that the existence of lots of stuff elsewhere
is not much of an answer to those like you who
prefer to do it in Stata anyway.
It's not obvious, however, that there is
one clear leader among techniques that
really is top of the should-be-implemented
list. StataCorp could easily devote a lot
of developer time just to adding numerous
commands and only partly satisfy user desires.
A Stata friend, not a Statalist member, has
just added to the repertoire of Stata programs
for missing data.
I'll not mention a name just in case that person
prefers not to go public yet, but I'll
ask privately whether the time is ripe
for an SSC release.
Nick
[email protected]
> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]]On Behalf Of
> Michael Ingre
> Sent: 21 January 2004 16:51
> To: [email protected]
> Subject: st: Efficient handling of missing data
>
>
> Dear Statalisters
>
> I need to calculate means and covariance matrices for use
> in structural
> equation modelling. This means a lot of variables and
> missing data is a
> serious problem. I need an efficient handling of missing data.
>
> -hotdeck- imputation is not efficient when there are many
> variables with
> missing data.
>
> To the best of my knowledge (!), the most valid method to
> handle missing
> data (MAR & MCAR) is to use Full Information Maximum
> Likelihood (FIML) or
> Multiple Imputation (MI) techniques. I know that there is a
> set of tools for
> analyzing MI-datasets available (SJ3-3 st0042) but there
> seem to be no tools
> available for generating them.
>
> I have also noticed a few .ado that handle missing data and
> uncertainties
> with an EM algorithm (STB-55 sg139, STB-57 sbe38, SJ2-1
> st0008). I know that
> SPSS uses the same kind of algorithm to estimate covariance
> matrices and
> means on data with missing values. LISREL also has an EM
> implementation. To
> me (at least) it seems likely that a similar procedure
> would be possible to
> .ado in Stata. But even if it was, the task is beyond my
> capabilities.
>
> Is there anybody out there who has an efficient solution
> for missing data?
>
> Is this a feature that Stata might consider to add to the
> official release?
>
> Is it only me?
>
> Thanks
>
> Michael
>
> -----------------
> PhD-student
> Department of Psychology
> Stockholm University &
> National Institute for
> Psychosocial Medicine
>
>
> PS
>
> I know it can be done in SAS, SPSS, AMOS, LISREL (PRELIS),
> Mx and others ...
> as well as with a few user written freeware NORM, amelial,
> EMCOV ... BUT! I
> would rather ado it in Stata. And I have my reasons.
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