Hi Andrew,

Unfortunately I do not have access to SAS, so that is simply not an option
for me, though I do welcome your clarification.  If this is a sensitive
topic perhaps I will abstain from mentioning it in future, but to me it was
a simple observation and not a value statement requiring qualification.

Perhaps I should put this another way: can anyone confirm that this
functionality does NOT exist or is NOT presently being worked on somewhere
within the R sphere?

Tyler



On Wed, Nov 3, 2010 at 5:49 PM, Andrew Robinson <
A.Robinson@ms.unimelb.edu.au> wrote:

> Hi Tyler,
>
> I think that there's something that you're missing.
>
> R is not motivated by comparisons with SAS or any package.  So, your
> impression that R was ahead of SAS or behind SAS is mistaken, or at
> least, it's your impression, so you are responsible for it.  R
> responds exactly to the community's needs because the community
> supports it.  If the functionality that you want isn't there, it's
> because noone else has wanted it badly enough to
>
> a) code it up, or
>
> b) pay someone else to code it up.
>
> If you want that function, and you know that SAS has it, then use SAS.
> If you want to use that function in R, then see the above two points.
>
> Good luck,
>
> Andrew
>
>
> On Wed, Nov 03, 2010 at 04:04:23PM -0400, Tyler Dean Rudolph wrote:
> > Indeed, in this case the correlation structure of the random effects is
> not
> > fully appreciated or known, in which case the standard errors are likely
> > underestimated.  The use of sandwich estimators should render variance
> > estimates, and therefore inference, somewhat more realistic.  While this
> is
> > currently possible with GEEs, that approach does not ask the same
> question
> > as a GLMM (i.e. marginal or "population" estimates vs. conditional or
> > "subject-specific" estimates).
> >
> > I used to think R updates were ahead of SAS upgrades in terms of new
> > approaches but apparently that is often not the case.  Does anyone have
> the
> > know-how required to implement this in R, or is there something I'm still
> > missing?
> >
> > Best,
> > Tyler
> >
> >
> > On Wed, Nov 3, 2010 at 9:12 AM, Dimitris Rizopoulos <
> > d.rizopoulos@erasmusmc.nl> wrote:
> >
> > > On 11/3/2010 1:57 PM, Doran, Harold wrote:
> > >
> > >> Out of curiosity, why would you want a sandwich estimator from lmer?
> That
> > >> estimator is typically used when the likelihood is misspecified, but
> you
> > >> still want standard errors that account for correlations among units
> within
> > >> a cluster.
> > >>
> > >> Since this is what lmer standard errors already account for, is there
> a
> > >> need for the sandwich?
> > >>
> > >
> > > well, it is possible that the random-effects structure that you have
> > > specified is not the correct one (i.e., in order to fully account for
> the
> > > correlations), and in this case it makes sense to use the sandwich
> estimator
> > > (of course, the sandwich estimator has its own problems, but this is
> > > probably another discussion...)
> > >
> > > Best,
> > > Dimitris
> > >
> > >
> > >
> > >  -----Original Message-----
> > >>> From: r-sig-mixed-models-bounces@r-project.org [mailto:
> > >>> r-sig-mixed-models-
> > >>> bounces@r-project.org] On Behalf Of Tyler Dean Rudolph
> > >>> Sent: Tuesday, November 02, 2010 4:41 PM
> > >>> To: r-sig-mixed-models@r-project.org
> > >>> Subject: [R-sig-ME] sandwich variance estimation using glmer?
> > >>>
> > >>> Are there any current functionalities in R that permit estimation of
> > >>> robust
> > >>> sandwich variances based on lmer (mixed model) objects??  I'm aware
> of
> > >>> the
> > >>> sandwich package and gee implementations but to my knowledge these
> are
> > >>> not
> > >>> yet compatible with mixed model objects.
> > >>>
> > >>> Apparently these are already implemented in SAS....
> > >>>
> > >>> Tyler
> > >>>
> > >>>        [[alternative HTML version deleted]]
> > >>>
> > >>> _______________________________________________
> > >>> R-sig-mixed-models@r-project.org mailing list
> > >>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> > >>>
> > >>
> > >> _______________________________________________
> > >> R-sig-mixed-models@r-project.org mailing list
> > >> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> > >>
> > >>
> > > --
> > > Dimitris Rizopoulos
> > > Assistant Professor
> > > Department of Biostatistics
> > > Erasmus University Medical Center
> > >
> > > Address: PO Box 2040, 3000 CA Rotterdam, the Netherlands
> > > Tel: +31/(0)10/7043478
> > > Fax: +31/(0)10/7043014
> > > Web: http://www.erasmusmc.nl/biostatistiek/
> > >
> >
> >       [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > R-sig-mixed-models@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>
> --
> Andrew Robinson
> Program Manager, ACERA
> Department of Mathematics and Statistics            Tel: +61-3-8344-6410
> University of Melbourne, VIC 3010 Australia               (prefer email)
> http://www.ms.unimelb.edu.au/~andrewpr              Fax: +61-3-8344-4599
> http://www.acera.unimelb.edu.au/
>

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