[R-sig-ME] nAGQ = 0
Rolf Turner
r.turner at auckland.ac.nz
Sun Sep 3 23:48:52 CEST 2017
On 04/09/17 03:48, Jonathan Judge wrote:
> Rolf:
>
> I have not studied this extensively with smaller datasets, but with
> larger datasets --- five-figure and especially six-figure n --- I have
> found that it often makes no difference.
> When uncertain, I have used a likelihood ratio test to see if the
> differences are likely to be material.
> My overall suggestion would be that if the dataset is small enough
> for this choice to matter, it is probably also small enough to solve the
> model through MCMC, in which case I would recommending using that,
> because the incorporated uncertainty often gives you better parameter
> estimates than any increased level of quadrature.
Thanks Jonathan.
(a) How small is "small"? I have 3 figure n's. I am currently mucking
about with two data sets. One has 952 observations (with 22 treatment
groups, 3 random effect reps per group). The other has 142 observations
(with 6 treatment groups and again 3 reps per group). Would you call
the latter data set small?
(b) I've never had the courage to try the MCMC approaches to mixed
models; have just used lme4. I guess it's time that I bit the bullet.
Psigh. This is going to take me a while. As an old dog I *can* learn
new tricks, but I learn them *slowly*. :-)
(c) In respect of the likelihood ratio test that you suggest --- sorry
to be a thicko, but I don't get it. It seems to me that one is fitting
the *same model* in both instances, so the "degrees of freedom" for such
a test would be zero. What am I missing?
Thanks again.
cheers,
Rolf
--
Technical Editor ANZJS
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276
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