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factor elimination for lmer models

2 messages · Austin Frank, Douglas Bates

Original
Austin Frank
# 
Hello!

I'll preface this by saying that this question may reveal some
fundamental misunderstanding on my part.  Thanks in advance for
clarification if there are things that I'm obviously not getting.
That said...

The Design library provides a function fastbw that does fast backwards
elimination of factors in a model.  This is a very useful function,
and I'm wondering what it would take to make it work with lmer or
lmer2-fitted models.

The function works on any model, m, where Varcov(m) is defined.
Varcov is a function from Hmisc that extracts the variance-covariance
matrix from certain kinds of fitted models.  Currently it works for
lm, glm, and multinom fitted models.

So, five questions:

1) Is there already a way to do automated factor elimination on an
   lmer-fitted model?

2) Would it be possible to write a function Varcov.lmer to extract the
   variance-covariance matrix from an lmer-fitted model?

3) Would it be possible to port the fastbw function from the Design
   library so that it would work on lmer models (without relying on
   Varcov from Hmisc)?

4) If both 2 and 3 are possible, which is the path of least
   resistance?

5) If neither 2 nor 3 is possible (the algorithm used in Design's
   fastbw is unsuitable for lmer models), is there an approach to
   factor elimination that is appropriate for these models?

If you folks get me started in the right direction, I'd be happy to
submit a patch to lme4 or languageR.
   
Thanks for your responses,
/au
Douglas Bates
#
On 3/20/07, Austin Frank <austin.frank at gmail.com> wrote:

            

      
      
      
    

        
Not that I know of.

            

      
      
      
    

        
I didn't go through the documentation for Varcov, which is part of a
large file related to transcan, in detail but it appears on simple
examples that Varcov produces the same result as vcov and there is a
vcov method for the lmer class.

            

      
      
      
    

        
It depends on what fastbw does.  That name seems to imply that it will
create the results from refitting a model omitting certain terms in
the model specification and it will do so without needing to refit.  I
don't think that would be possible for lmer models because when you
omit a term in the fixed-effects specification you will change the
estimates of the variance components.  The results from the vcov
method are conditional on the values of the variance components.