[R-sig-ME] glmmTMB deviance enquiry

[Ben Bolker]

    The deviance is twice the negative log-likelihood; if the deviance 
is D for a model with p parameters, then AIC = D + 2*p.  The deviance is 
an *unpenalized* measure of goodness of fit (badness of fit actually - 
lower deviance means better fit).

    There's no need to report deviance in a paper if it's not useful to 
you or your readers. The deviance for a model alone is not particularly 
useful; you can use the deviances for several nested models to compute 
likelihood ratio rests (via anova()), or you can use deviance as the 
basis for computing AIC or BIC.

   Hope that helps.

   Ben Bolker

On 2023-03-07 9:08 a.m., Rion Lerm via R-sig-mixed-models wrote:
> I reported, in a paper, on the *Deviance* value for model fit as produced
> by the *glmmTMB* function.
> 
> Please explain how this value is computed, and what are the pros/cons of
> this compared to e.g., AIC. I need to comprehend its use and explain the
> how and why? to a reviewer and possibly the paper's readers.
> 
> Regards and thanks in advance,
> 
> *Rion Lerm*
> 
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-- 
Dr. Benjamin Bolker
Professor, Mathematics & Statistics and Biology, McMaster University
Director, School of Computational Science and Engineering
(Acting) Graduate chair, Mathematics & Statistics
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