[R] Help to conduct a random factor analysis with binomial response

[Ross Darnell]

Leif Egil Loe <l.e.loe at bio.uio.no> writes:

> Dear users of the R mailing list,
> 
> I am a ph.d. student in biology working on red deer in Norway, who
> would like to conduct an analysis with random factor where the
> response is binomially distributed. This cannot be conducted in
> S-plus, and I was told by others that it may be possible in
> R. However, I soon got into trouble which I hope you can help me to
> solve.
> 
> 
> My model is on this form:
> cbind(success,1-success) ~ variable 1 (numeric) + variable 2 (numeric)
> + variable 3 (factor) + variable 4 (factor). I have only one random
> factor, variable 5 (factor).
> 

[...]

I wrote a function in R that uses the EM algorithm for nonparametric
ML estimation in GLMs decribed by Aitkin (Biometrics 1999) first used
by Hinde ad Wood (1987). This is a generalization of the random
effects models for overdispersion in GLMs. The nice feature of this
approach is that you concurrently model normal as well as unknown
mixing distributions.  The algorithm alows for only one random effect.

The R function is based on the GLIM macro defined by AItkin and
Francis (1995 The GLIM Newsletter).

I would gladly run your data through for you.

Ross Darnell
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