R help - Aug 2006 - New version of glmmML

A new version, 0.65-1, of glmmML is now on CRAN. It is a major rewrite
of the inner structures, so frequent updates (bug fixes) may be
expected for some time.

News:

* The Laplace and adaptive Gauss-Hermite approximations to the log
likelihood function are fully implemented. The Laplace method is made
the default. It should give results you can compare to the results
from 'lmer' (for the models that glmmML can handle).

* Binomial responses can now be represented as a two-column matrix
with No. of successes and No. of failures, respectively, as in glm.

* New functions: 'ghq' for calculating the constants used in the
Gauss-Hermite quadrature. 'extractAIC.glmmML', which makes it possible
to use functions like 'dropterm' (MASS) on glmmML fits.

* There are three choices of distribution for the random effects:
'gaussian' (default), 'logistic', and 'cauchy'.

* The 'conditional' bootstrap is removed, so the only choice now is
the parametric bootstrap.

* The 'posterior.means' are no longer calculated, leaving only the
'posterior.modes' as 'predictions' of the random effects.

As usual, feedback is more than welcome!

G?ran

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Hi G?ran,
>>>>> "GB" == G?ran Brostr?m <goran.brostrom at
gmail.com>
>>>>>     on Mon, 21 Aug 2006 11:12:49 +0200 writes:
    GB> A new version, 0.65-1, of glmmML is now on CRAN. It is a major
rewrite
    GB> of the inner structures, so frequent updates (bug fixes) may be
    GB> expected for some time.


    GB> News:

    [............]

Sorry for my lazy question :

   What does the package do that lmer() does not?

I do know that you are a smart person so I know I will get a non-trivial
answer.  The main reason for this e-mail is really to encourage you (and
all other 'R-packages' posters) to do the following in each
posting to R-packages:

1) [One paragraph:]
  What does the package do // why do you see a need for the
  package // what's the bigger context ?

2) [another paragraph (or two...):]
  News  etc

Since the R-packages archives are relatively prominently listed
as part of "News" on the R project website, (and also since I
encourage ``everyone'' to subscribe to R-packages,)

I think the extra information in "1)" above would be appropriate
for every posting to R-packages.

Martin Maechler, ETH Zurich