[R] Marginal effects of ZINB models

[Achim Zeileis]

On Mon, 10 Dec 2012, Jeremy Goss wrote:

> Dear all,
> I am modeling the incidence of recreational anglers along a stretch of
> coastline, and with a vary large proportion of zeros (>80%) have chosen to
> use a zero inflated negative binomial (ZINB) distribution. I am using the
> same variables for both parts of the model, can anyone help me with R code
> to compute overall marginal effects of each variable?
>
> My model is specified as follows:
>
> ZINB <- zeroinfl(Tot.Anglers ~ Location + Season + Daytype + Holiday.not +
> CPUE + ShoreType + Access + Source.pop + WindSpeed + offset(beat_length),
> dist="negbin", data=anglers)

We haven't implemented any marginal effects for hurdle/zeroinfl because I 
rarely find these useful in practice. Also, you probably would need 
several marginal effects for the same variable because you might want to 
describe the effect on the zero-inflation, on the count component, and on 
the mixture of both.

But with the building blocks provided by hurdle/zeroinfl you can compute 
many of the quantities that are potentially of interest "by hand". For 
hurdle models, there is some discussion of this in the following posting:
https://stat.ethz.ch/pipermail/r-help/2012-January/300949.html

Best,
Z

>
> Many thanks,
> Jeremy
>
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>
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