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Re: st: Postestimation procedures multiple data sets


From   Maarten buis <maartenbuis@yahoo.co.uk>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Postestimation procedures multiple data sets
Date   Mon, 27 Apr 2009 08:50:37 +0000 (GMT)

--- On Mon, 27/4/09, fjgallo@mac.com wrote:
> I performed an ice command that generated 5-data sets (each
> n = 3,300). I followed up with a mim run (regress). I am
> using Stata 10. I read the ice and mim command help files.
> It appears to me that I cannot obtain an R^2 value for the
> overall mim run. It also seems to me that I cannot perform
> any multivariate diagnostics for assumption violations on
> that run of the data. Is this correct? 

I would limit the model checking to graphical checks (I 
would do so anyhow even if I used non-imputed data, but 
that is another issue and opions differ on this). An 
example of how you could do that is shown below:
 
*---------- begin example ----------------
sysuse auto, clear
gen miss = missing(rep78, mpg, price)
ice rep78 mpg price, clear m(5) 

mim, storebv: reg price mpg rep78
predict xb
gen resid = xb -  price

twoway scatter resid mpg             ///
       if miss == 0 ,                ///
       by(_mj, compact) ||           ///
       scatter resid mpg             ///
       if miss == 1,                 ///
       mcolor(red)                   ///
       legend(order(1 "observed"     ///
                    2 "imputed"))    ///
       ytitle(residual) ||           ///
       mband resid mpg
*-------------- end example -----------------	

As to R^2, see the opion of Don Rubin here:
http://www.mail-archive.com/impute@lists.utsouthwestern.edu/msg00102.html

and my interpretation of it in Stata code here:
http://www.stata.com/statalist/archive/2007-04/msg00900.html

Hope this helps,
Maarten

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

http://home.fsw.vu.nl/m.buis/
-----------------------------------------


      

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