[R] Model averaging using QAICc

Kamil Bartoń k.barton at abdn.ac.uk
Sat Jan 18 01:36:11 CET 2014

On 2014-01-15 11:00, r-help-request at r-project.org wrote:
> Date: Wed, 15 Jan 2014 16:39:17 +1000
> From: Diana Virkki<d.virkki at griffith.edu.au>
> To:r-help at r-project.org
> Subject: [R] Model averaging using QAICc
> Message-ID:
>       <CAL6nRQcAyN-3SVeZSMXoJq=vsXoTPG3e0PRWjw7iu7g20B+AWQ at mail.gmail.com>
> Content-Type: text/plain
> Hi all,
> I am having some trouble running GLMM's and using model averaging with
> QAICc.
> Let me know if you need more detail here:
> I am trying to run GLMM's on count data in the package glmmADMB with a
> negative binomial distribution due to overdispersion. The dispersion
> parameter has now reduced to 2.679 for the global model (from a dispersion
> parameter of 27.507 with a poisson distribution), and I am not sure if this
> is still considered too high for running the models?
> I would like to try to use QAICc's for model selection and model averaging
> with the package MuMIn. I have so far been able to produce a QAICc output
> only for the models. I read that model averaging with QAICc can be done in
> MuMIn but cannot find the syntax to get these outputs, including the model
> weightings, parameter estimates, confidence intervals, and relative
> variable importance.

Use argument 'rank' to provide the information criterion to use:
- with 'dredge': rank = "QAICc", chat = <c-hat>
- with 'model.sel' and 'model.avg' : rank = "QAICc", rank.args =
list(chat = <c-hat>)

See example(QAICc) and example(model.avg)


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