From: Douglas Bates <bates_at_stat.wisc.edu>

Date: Tue 12 Sep 2006 - 14:58:11 GMT

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Wed Sep 13 01:08:53 2006

Date: Tue 12 Sep 2006 - 14:58:11 GMT

On 9/11/06, Manuel Morales <Manuel.A.Morales@williams.edu> wrote:

> On Mon, 2006-09-11 at 11:43 -0500, Douglas Bates wrote:

*> > On 9/10/06, Andrew Robinson <A.Robinson@ms.unimelb.edu.au> wrote:
**> > > On Thu, Sep 07, 2006 at 07:59:58AM -0500, Douglas Bates wrote:
**> > >
**> > > > I would be happy to re-institute p-values for fixed effects in the
**> > > > summary and anova methods for lmer objects using a denominator degrees
**> > > > of freedom based on the trace of the hat matrix or the rank of Z:X if
**> > > > others will volunteer to respond to the "these answers are obviously
**> > > > wrong because they don't agree with <whatever> and the idiot who wrote
**> > > > this software should be thrashed to within an inch of his life"
**> > > > messages. I don't have the patience.
**> > >
**> > > This seems to be more than fair to me. I'll volunteer to help explain
**> > > why the anova.lmer() output doesn't match SAS, etc. Is it worth
**> > > putting a caveat in the output and the help files? Is it even worth
**> > > writing a FAQ about this?
**> >
**> > Having made that offer I think I will now withdraw it. Peter's
**> > example has convinced me that this is the wrong thing to do.
**> >
**> > I am encouraged by the fact that the results from mcmcsamp correspond
**> > closely to the correct theoretical results in the case that Peter
**> > described. I appreciate that some users will find it difficult to
**> > work with a MCMC sample (or to convince editors to accept results
**> > based on such a sample) but I think that these results indicate that
**> > it is better to go after the marginal distribution of the fixed
**> > effects estimates (which is what is being approximated by the MCMC
**> > sample - up to Bayesian/frequentist philosophical differences) than to
**> > use the conditional distribution and somehow try to adjust the
**> > reference distribution.
**>
**> Am I right that the MCMC sample can not be used, however, to evaluate
**> the significance of parameter groups. For example, to assess the
**> significance of a three-level factor? Are there better alternatives than
**> simply adjusting the CI for the number of factor levels
**> (1-alpha/levels).
*

I would recommend calculating this for a couple of samples to check on the reproducibility.

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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Wed Sep 13 01:08:53 2006

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