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Re: st: Re: Factor analysis after multiple imputation in STATA


From   tang5@purdue.edu
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Re: Factor analysis after multiple imputation in STATA
Date   Tue, 17 Jul 2007 12:42:36 -0400

Then the analysis would be only on the observed data? Or is there any hidden 
imputation type of process going on? Thanks!

  SR Millis <srmillis@yahoo.com>:

> As an alternative to imputation, the AMOS software
> computes full information maximum likelihood (FIML)
> estimates.  When data are only missing at random
> (MAR), the FIML approach yield parameter estimates
> that are efficient and consistent.  However, multiple
> imputation methods can produce severely biased
> results.
> 
> Scott Millis
> 
> 
> > > ///
> > > Woolton,
> > > 
> > > You could check Schafer, J.L. (1997), Analysis of
> > Incomplete Multivariate 
> > > Data, New York: Chapman and Hall, as primary
> > reference for Missing Data and 
> > > how to run EM. Joe has an executable for Windows
> > that computes EM algorithm 
> > > (http://www.stat.psu.edu/~jls/norm203.exe), it is
> > very fast and friendly. 
> 
> Scott R Millis, PhD, MEd, ABPP (CN,CL,RP), CStat
> Professor & Director of Research
> Dept of Physical Medicine & Rehabilitation
> Wayne State University School of Medicine
> 261 Mack Blvd
> Detroit, MI 48201
> 
> / `--'( 
> < [] []////////|:::)
> \_.--.( 
> 
> Email:  smillis@med.wayne.edu
> Tel: 313-993-8085
> Fax: 313-966-7682
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