[R-sig-ME] sandwich variance estimation using glmer?

[Andrew Robinson]

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 at 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 at r-project.org [mailto:
> >>> r-sig-mixed-models-
> >>> bounces at r-project.org] On Behalf Of Tyler Dean Rudolph
> >>> Sent: Tuesday, November 02, 2010 4:41 PM
> >>> To: r-sig-mixed-models at 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 at r-project.org mailing list
> >>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> >>>
> >>
> >> _______________________________________________
> >> R-sig-mixed-models at 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 at 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/