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Can I use the Anova (type II) to test significance in my negative binomial regression?

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I have fitted a binomial regression (glm.nb using the MASS package) to my data.

I have two questions and would be very thankfull if you could answer any of them:

1a) Can I use the Anova (type II, car package) to analyse which explanatory variables are significant? Or should I use the summary() function?

I know theta is assumed to be fixed in the Anova, which might be a problem. I however get completely different outcomes for Anova test and summary, and based on visualisation of the data I feel that Anova is more accurate.

1b) When using the Anova, both an F-test and a chisquare test give pretty similar results - is there any of these tests that is preferred for a negative binomial regression? Or is there any way to find out which test represents the most likely results? Based on visualisation, the F test seems to fit best.

2) When looking at the diagnostic plots, my qq-plot looks kinda off. I am wondering if this is fine - since the negative binomial is different from the normal distribution? Or should the residuals still be normally distributed?

Diagnostic plots image


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