[R-sig-ME] ZINB model validation and interpretation

Christopher David Desjardins cddesjardins at gmail.com
Wed Sep 20 20:32:48 CEST 2017

Hi Miriam,

As Ben mentioned, this isn't a mixed effects model. But what you've done is
reasonable and would second Ben's framework for investigating your model.

I am assuming you're using the pscl library? If so, Achim Zeileis has a
vignette that goes over these models which you might find helpful:

I investigated these models under simulation in my dissertation and if
you've like more references or have specific question, please feel free to
contact me off list.

On Wed, Sep 20, 2017 at 11:24 AM, Ben Bolker <bbolker at gmail.com> wrote:

> This isn't actually a mixed-model question as far as I can tell, but
> I'll take a stab at it.  (https://stats.stackexchange.com is probably
> the best option for follow-ups, as R-help isn't for general statistics
> questions.)
> Your approach seems not-crazy to me, although I would probably be
> lazier/slopper and compare all four cases (P, NB, ZIP, ZINB) in a
> single AIC(c) table. In any case, there are very basic issues with
> either P vs NB or ZIP vs ZINB tests based on any of the standard
> approaches (Vuong, *IC, likelihood ratio test) that come from the fact
> that one of the pair of models is on the boundary of the feasible
> space, see e.g.
> https://stats.stackexchange.com/questions/182020/zero-
> inflated-poisson-regression-vuong-test-raw-aic-or-bic-
> corrected-results/217869
> For validity and robustness, I would suggest more "impressionistic"
> diagnostics (inspect residuals for independence of predictors, lack of
> heteroscedasticity; look for influential/outlier residuals; compare
> patterns of predictions with patterns in raw data for evidence of
> unexpected patterns). If you want more formal tests, try generating
> posterior predictive simulations of quantities that are important to
> you and see if they match the observed values of those quantities.
> On Mon, Sep 18, 2017 at 6:25 PM,  <miriam.alzate at unavarra.es> wrote:
> > Hello,
> > I am working with a ZINB model in R. To validate it, I first did a VUONG
> > test to compare it with a standard NB model. The result is that the ZINB
> > is better than the NB. Then, I compared the ZINB to a ZIP model,
> comparing
> > the AIC index and the log-likelihood and I also get that the ZINB fits
> > better than the ZIP.
> >
> > However, I would like to know if I should take other tests into
> > consideration to show the validity and robustness of my model.
> >
> > On the other hand, I would like to know if I can interpret the
> > coefficients directly from the model result or I should compute the Odds
> > ratios.
> >
> > Thanks a lot,
> >
> > Miriam
> >
> > _______________________________________________
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> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
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