glmmTMB deviance enquiry
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* SAEON Ndlovu C: 076 913 8381 W: 013 735 3536 SAEON / Scientific Services, Kruger National Park Gate, Phalaborwa, South Africa South African Environmental Observation Network Website <https://ndlovu.saeon.ac.za/> & Location of our offices <https://www.google.co.za/maps/place/SAEON+Ndlovu+Node/@-23.9447244,31.164957,18z/data=!4m5!3m4!1s0x1ec36ec96261cfb7:0xb89a27144ba0ca2a!8m2!3d-23.9450103!4d31.1652626> My research profiles: *ResearchGate* <https://www.researchgate.net/profile/Rion-Lerm> *ORCID <https://orcid.org/0000-0002-9992-2093>* *Google Scholar <https://scholar.google.com/citations?user=JV5d7E4AAAAJ&hl=en>*
Dr. Benjamin Bolker Professor, Mathematics & Statistics and Biology, McMaster University Director, School of Computational Science and Engineering (Acting) Graduate chair, Mathematics & Statistics > E-mail is sent at my convenience; I don't expect replies outside of working hours.