Then the analysis would be only on the observed data? Or is there any hidden
imputation type of process going on? Thanks!
SR Millis <[email protected]>:
> 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
>
> / `--'(
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