Cheking for outliers after fitting a glmmTMB
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 [[alternative HTML version deleted]]
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