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Re: st: mi and ice commands
From
Aggie Chidlow <[email protected]>
To
[email protected]
Subject
Re: st: mi and ice commands
Date
Wed, 9 Mar 2011 21:52:45 +0000
Dear Yulia,
Thank you for your explanations.I really appreciate them.
Further, I have to say, I am founding your ppt (which I found on-line)
very useful as well.
One more thing, if you don't mind.
I am currently running "mi estimate: regress y x1 x2 x3"
As I am used to reporting R2 for my results, I can't see it for the
"mi estimate" command. Apologies for a silly question, but is R2 not
reported in "mi estimate"
In addition, would you mind telling me what are the main statistics
that should be reported after running "mi estimate: regress y x1 x2
x3"?
Many thanks in advance.
Aggie
On Wed, Mar 9, 2011 at 2:41 AM, Yulia Marchenko, StataCorp
<[email protected]> wrote:
> Aggie Chidlow <[email protected]> asks about the difference between
> Stata's official command -mi- and the user-written command -ice-:
>
>> As I am new to "mi" and "ice" commands I have been reading about them quite
>> extensively. However I am still a bit confused,and as a result I would
>> really appreciate if somebody clarified the following to me:
>>
>> a) what is the difference between "mi" and "ice" ?
>
> The -mi- command performs all steps of multiple-imputation
> analysis: imputation, data manipulation, and final primary-data
> analysis.
>
> For the imputation step, -mi impute- supports several univariate
> imputation methods and multivariate imputation based on
> the multivariate normal distribution (Schafer 1997). See
>
> http://www.stata.com/capabilities/mi.html
>
> for the full list of capabilities of -mi-.
>
> The -ice- command performs the first step of multiple-imputation
> analysis: imputation. -ice- performs multivariate imputation
> using chained equations (van Buuren et al. 1999). This method is
> currently not available in -mi impute-.
>
> After imputation using -ice-, the other steps of multiple-imputation
> analysis can be performed by the user-written command -mim-, or
> the imputed data from -ice- can be imported into the -mi- framework
> using -mi import ice-.
>
> The following FAQ provides full details:
>
> http://www.stata.com/support/faqs/stat/mi_ice.html
>
>
>> b) what is the preffered "mi style" for a panel data?
>
> There is no preferred mi style specific for panel data. In general, I like
> to work in -wide- because I often compare my multiple-imputation results to
> the complete-cases analysis and this is the most convenient style for that.
> Depending on how you impute your panel data (see, for example,
> http://www.stata.com/support/faqs/stat/impute_cluster.html for some
> strategies), style -mlong- may be more convenient.
>
>
> References:
>
> Schafer, J. L. 1997. Analysis of Incomplete Multivariate Data. Boca Raton, FL:
> Chapman & Hall/CRC.
>
> van Buuren, S., H. C. Boshuizen, and D. L. Knook. 1999. Multiple imputation of
> missing blood pressure covariates in survival analysis. Statistics in
> Medicine 18: 681–694.
>
>
> -- Yulia
> [email protected]
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
*
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