[R-sig-ME] Cheking for outliers after fitting a glmmTMB
Fox, John
jfox @ending from mcm@@ter@c@
Mon May 21 14:43:53 CEST 2018
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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