glmmTMB deviance enquiry
Thank you @bbolker at gmail.com <bbolker at gmail.com> for your elaborate response. I am using the Deviance values in this manner to compare model fit. Here, I selected for the model with second to smallest Deviance values. May it be presented like this as I feel it is important to display how a model was selected from various models (the reason for selecting the second to smallest values aren't explained here as is the details of this work): *Model predictor fixed effects* *SR.asymp* *SES.FRic* *SES.PD* Deviance Tree + Shrub + Grass + Bare ground + Infrastructure + Seasonal water + Permanent water 760.4 | 1,463.6 172.1 | 319.6 206.7 | 420.7 Tree + Shrub + Bare ground + Infrastructure + Seasonal water + Permanent water *766.3 | 1467.7* *179.0 | 325.2* *207.3 | 421.3* Tree + Shrub + Grass + Bare ground 777.1 | 1,520.3 179.4 | 368.7 229.3 | 441.5 Tree + Shrub + Grass + Bare ground + Infrastructure 776.8 | 1,484.3 179.0 | 323.0 217.2 | 424.2 Tree + Shrub + Grass + Bare ground + Seasonal water + Permanent water 760.5 | 1,498.4 172.3 | 363.2 216.8 | 439.9 Importantly, is there any literature I can cite on Deviance and its use? If so, please supply a DOI. Regards/Groete, *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>*
On Tue, 7 Mar 2023 at 16:32, Ben Bolker <bbolker at gmail.com> wrote:
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 <
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
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