[R-sig-ME] Fwd: same old question - lme4 and p-values

[David Afshartous]

On 4/7/08 7:46 PM, "Simon Blomberg" <s.blomberg1 at uq.edu.au> wrote:

> On Mon, 2008-04-07 at 20:47 +1000, John Maindonald wrote:
> [ snip ]
>> 
>> Douglas's mcmcsamp() has advanced the state of the art
>> for multi-level models, offering an approach that had not
>> previously been readily available.  It is anyone's guess
>> where it, and statistics and graphs that it makes readily
>> possible, will in the course of time fit among styles of
>> presentation that application area people find helpful.
> 
> Well, it's been possible to easily implement multi-level models in BUGS
> using MCMC for a long time. Would you agree that BUGS is readily
> available? :-) Doug has made it more convenient for R users, but I'm not
> sure it has necessarily advanced the state of the art. Maybe brought R
> up to speed (but ahead of other software which tends to start with the
> letter S).
> 

Just catching up on this discussion, but RE BUGS, although I'm not an
experience BUGS user I've been running some simulations for various mixed
effects models in both lmer and BUGS (via bugs() function in R2WinBugs), and
it seems that lmer is much more stable than BUGS for the types of models
I've been fitting.  Do others that use both have similar experience?


> Simon.
> 
>> 
>> John Maindonald             email: john.maindonald at anu.edu.au
>> phone : +61 2 (6125)3473    fax  : +61 2(6125)5549
>> Centre for Mathematics & Its Applications, Room 1194,
>> John Dedman Mathematical Sciences Building (Building 27)
>> Australian National University, Canberra ACT 0200.
>> 
>> 
>> On 7 Apr 2008, at 12:05 PM, David Henderson wrote:
>> 
>>> Hi John:
>>> 
>>>> For all practical purposes, a CI is just the Bayesian credible
>>>> interval that one gets with some suitable "non-informative prior".
>>>> Why not then be specific about the prior, and go with the Bayesian
>>>> credible interval?  (There is an issue whether such a prior can
>>>> always be found.  Am right in judging this no practical consequence?)
>>> 
>>> 
>>> What?  Could you explain this a little more?  There is nothing
>>> Bayesian about a classical (i.e. not Bayesian credible set or
>>> highest posterior density, or whatever terminology you prefer) CI.
>>> The interpretation is completely different, and the assumptions used
>>> in deriving the interval are also different.  Even though the
>>> interval created when using a noninformative prior is similar to a
>>> classical CI, they are not the same entity.
>>> 
>>> Now, while i agree with the arguments about p-values and their
>>> validity, there is one aspect missing from this discussion.  When
>>> creating a general use package like lme4, we are trying to create
>>> software that enables statisticians and researchers to perform the
>>> statistical analyses they need and interpret the results in ways
>>> that HELP them get published.  While I admire Doug for "drawing a
>>> line in the sand" in regard to the use of p-values in published
>>> research, this is counter to HELPING the researcher publish their
>>> results.  There has to be a better way to further your point in the
>>> community than FORCING your point upon them.  Education of the next
>>> generation of researchers and journal editors is admittedly slow,
>>> but a much more community friendly way of getting your point used in
>>> practice.
>>> 
>>> Just my $0.02...
>>> 
>>> Dave H
>>> --
>>> David Henderson, Ph.D.
>>> Director of Community
>>> REvolution Computing
>>> 1100 Dexter Avenue North, Suite 250
>>> 206-577-4778 x3203
>>> DNADave at Revolution-Computing.Com
>>> http://www.revolution-computing.com
>>> 
>> 
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