RE: st: mi impute chained

[chong shiauyun <shiauyun416@hotmail.com>]

Hi Richard, 
thanks for your suggestions. I will check the missing data again and keep you updated.

Cheers
Shiau

----------------------------------------
> Date: Fri, 2 Nov 2012 09:33:01 -0500
> To: statalist@hsphsun2.harvard.edu; statalist@hsphsun2.harvard.edu
> From: richardwilliams.ndu@gmail.com
> Subject: RE: st: mi impute chained
>
> At 03:28 AM 11/2/2012, chong shiauyun wrote:
> >I used -force- in my MI model it resulted in a number of missing
> >values which can't be imputed. For example, I have 7000 missing data
> >on IQ and only 1800 are imputed.
>
> Do you have hard missing or soft missing? From the manual:
>
> hard missing and soft missing. A hard missing value is a value of .a,
> .b, : : : , .z in m = 0 in an imputed variable. Hard missing values
> are not replaced in m > 0. A soft missing value is a value of . in m
> = 0 in an imputed variable. If an imputed variable contains soft
> missing, then that value is eligible to be imputed, and perhaps is
> imputed, in m > 0. Although you can use the terms hard missing and
> soft missing for passive, regular, and unregistered variables, it has
> no special significance in terms of how the missing values are treated.
>
> >
> >
> >I know this is because of the missingness of predictors in my model
> >but I don't understand why is happens because I have already
> >specified to use -mi impute chained- to impute other predictors as well.
> >
> >is there any ways to overcome this problem?
> >
> >This is how the IQ conditional model looks like:
> >
> >truncreg totaliq birthweight i.smkpreg i.marist i.matdepr i.homeown3
> >i.alcpreg3 i.hhcrowd i.ednmatpat i.findiff i.ethnicity i.scmatpat3
> >i.mumhealth i.breastfed i.social verbiq perfiq mumiq tempcatwlc_i
> >tempcatclc_i sex mumage babygestation , ll(45) ul(151) noisily
> >
> >Many thanks
> >
> >Shiau
> >
> > > Date: Wed, 31 Oct 2012 08:48:39 -0400
> > > Subject: Re: st: mi impute chained
> > > From: jvverkuilen@gmail.com
> > > To: statalist@hsphsun2.harvard.edu
> > >
> > > On Wed, Oct 31, 2012 at 4:54 AM, chong shiauyun
> > <shiauyun416@hotmail.com> wrote:
> > > > Hi,
> > > >
> > > > thanks for your advice.
> > > > I simplified my MI model by excluding some interactions and
> > reduced some of my variables. It works fine. However, I am concern
> > that I have to use the -force- option to make the model works. It
> > am quiet reluctant to drop all of the interactions seeing that it
> > may affect the relationship between the exposure and the outcome
> > which I am interested in.>
> > >
> > > I've used -force- and I think it works OK but check using
> > > -midiagplots-, which you can download.
> > >
> > > As to the interactions, if they're very collinear with the other
> > > variables you have in the model they're not adding anything. You can
> > > experiment with dropping or adding variables and keep checking with
> > > -midiagplots- to determine how things are working. Remember, the idea
> > > in MI is not to have a perfectly reconstructed dataset but to
> > > optimally preserve insofar as is possible the information you do have.
> > >
> > > *
> > > * For searches and help try:
> > > * http://www.stata.com/help.cgi?search
> > > * http://www.stata.com/support/faqs/resources/statalist-faq/
> > > * http://www.ats.ucla.edu/stat/stata/
> >
> >*
> >* For searches and help try:
> >* http://www.stata.com/help.cgi?search
> >* http://www.stata.com/support/faqs/resources/statalist-faq/
> >* http://www.ats.ucla.edu/stat/stata/
>
> -------------------------------------------
> Richard Williams, Notre Dame Dept of Sociology
> OFFICE: (574)631-6668, (574)631-6463
> HOME: (574)289-5227
> EMAIL: Richard.A.Williams.5@ND.Edu
> WWW: http://www.nd.edu/~rwilliam
>
> *
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> * http://www.ats.ucla.edu/stat/stata/
 		 	   		  
*
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