[R-sig-ME] Cheking for outliers after fitting a glmmTMB

[Mollie Brooks]

Hi Irene,

Some residual diagnostics can be done with the DHARMa package, but maybe not Cook’s distance and leverage. 

Here’s the main documentation
https://cran.r-project.org/web/packages/DHARMa/vignettes/DHARMa.html <https://cran.r-project.org/web/packages/DHARMa/vignettes/DHARMa.html>

and here’s a discussion about using it with glmmTMB
https://github.com/florianhartig/DHARMa/issues/16 <https://github.com/florianhartig/DHARMa/issues/16>

cheers,
Mollie

———————————
Mollie E. Brooks, Ph.D.
Research Scientist
National Institute of Aquatic Resources
Technical University of Denmark

> On 21May 2018, at 14:43, Fox, John <jfox at mcmaster.ca> wrote:
> 
> Dear Irene,
> 
> You're apparently trying to use the leveragePlot() function in the car package. That doesn't plot residuals vs. hat-values (leverages) but is rather a variation on added-variable plots. 
> 
> The car package does have some influence diagnostics for mixed models, but unfortunately only for models fit with functions in the lme4 and nlme packages. See ?influence.mixed.models . Perhaps you can adapt our code to the glmmTMB package.
> 
> I hope this helps,
> John
> 
> -----------------------------
> John Fox, Professor Emeritus
> McMaster University
> Hamilton, Ontario, Canada
> Web: socialsciences.mcmaster.ca/jfox/
> 
> 
> 
>> -----Original Message-----
>> From: R-sig-mixed-models [mailto:r-sig-mixed-models-bounces at r-
>> project.org] On Behalf Of Irene Rojo
>> Sent: Monday, May 21, 2018 4:52 AM
>> To: r-sig-mixed-models at r-project.org
>> Subject: [R-sig-ME] Cheking for outliers after fitting a glmmTMB
>> 
>> Dear all,
>> 
>> I am trying to check the assumptions after fitting a glmm with the glmmTMB
>> package.
>> 
>> However, I don't know how to get the Residuals vs Leverage plot and Cook's
>> distance. Neither the "leveragePlot(model)" nor "leverage.plot(model)"
>> functions do work with an object of class glmmTMB. Can anyone give some
>> advice of how can I get it?
>> 
>> Thank you so much,
>> 
>> Irene
>> 
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>> 
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