[R] FIML in lme

[Doran, Harold]

I'm not sure you are correct on this. Other texts on multilevel models
(e.g., Raudenbush and Bryk, Kreft and Deeuw, and Singer & Willett) all
use FiML as a synonym for ML. In fact, Kreft and Deleeuw go as far to
even state they are the same thing (see page 131).

When you run a model in HLM selecting "Full Maximum Likelihood" and
method="ML" in lme, the results, including all fixed effects, variance
components, empirical bayes residuals, degrees of freedom are exactly
the same.

So, I think Doug is correct in that ML == FiML. 

Harold

-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of F Z
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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