[R] FIML in lme
Iyue Sung
isung at affinnova.com
Mon Aug 30 19:02:31 CEST 2004
You might want to look into multiple imputation methods as an
alternative (see work by Don Rubin and Joe Schafer).
I know Schafer has a library for S-plus, but not sure about R.
> -----Original Message-----
> From: F Z [mailto:gerifalte28 at hotmail.com]
> Sent: Monday, August 30, 2004 12:52 PM
> To: chris at lordsutch.com; r-help at r-project.org; bates at stat.wisc.edu
> Subject: Re: [R] FIML in lme
>
> Thanks to Douglas Bates and Christopher Lawrence for their responses.
> Christopher is right, that is what I was asking about. I guess that
there
> is no implementation of FIML in R. Would this be a worthy method to
> include
> in R? I don't really use this method so I would say no but maybe some
> people think in a different way (For example SAS users trying ot move
to
> R)?
>
> Respectfully
>
> Francisco
>
>
> >From: Chris Lawrence <chris at lordsutch.com>
> >To: R-Help <r-help at r-project.org>
> >Subject: Re: [R] FIML in lme
> >Date: Sat, 28 Aug 2004 02:29:08 -0500
> >
> >On Aug 27, Douglas Bates wrote:
> > > F Z wrote:
> > > >I was asked if lme can use FIML (Full Information Maximum
Likelihood)
> > > >instead of REML or ML but I don't know the answer. Does anybody
know
> >if
> > > >this is implemented in R?
> > >
> > > To the best of my knowledge, FIML is ML so the answer is yes.
> > >
> > > For example, the phrase "Full Information Maximum Likelihood" is
used
> in
> > > Singer and Willett (2004) "Applied Longitudinal Data Analysis"
(Oxford
> > > University Press) as a synonym for maximum likelihood.
> >
> >I have seen FIML used to refer to a type of ML estimation where a
> >missing data treatment is included in the estimation procedure
> >(parameter estimates are derived from incomplete cases for only the
> >variables present in the case, rather than simply discarding the
> >cases), at least in the latent-variable SEM context, specifically in
> >AMOS. This may be what Francisco is getting at.
> >
> >To my knowledge, no R packages implement this sort of "FIML", for any
> >class of models, although there are other available missing data
> >treatments (EM, MCMC estimation).
> >
> >
> >Chris
> >--
> >Christopher N. Lawrence, Ph.D.
> >Visiting Assistant Professor of Political Science
> >Millsaps College
> >1701 N. State St
> >Jackson, MS 39210
> >(601) 974-1438 / lawrecn at millsaps.edu
> >
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