[R-sig-ME] Odd ANOVA degrees of freedom with ZI component of glmmTMB model

[Elliot Johnston]

Thanks for getting back to me Ben and John. As I was making a reproducible
example for this thread, I dropped all of the dataframe columns not used in
the analysis and ended up trimming the dataframe down from 35 columns to 6.
The zero-inflated ANOVA output now appears more sensical:

> car::Anova(m1, component = "zi")

Analysis of Deviance Table (Type II Wald chisquare tests)

Response: Count

                                 Chisq   Df  Pr(>Chisq)
Time_Period            1.9271  2    0.38154
Assignment             1.5043  1    0.22001
Time_Period:Assignment 7.9605  2    0.01868 *

The statistics for the interaction are the same as before, but the Time
Period and Assignment terms now make more sense. No observations were
dropped and the model specification remained the same, I just dropped a
number of columns. Seems strange, but I have the desired output so I don't
feel the need to troubleshoot the source of the error at this point. Hope
that's alright with you both. Thanks again for getting back to me.

-Elliot

On Wed, Jan 11, 2023 at 2:52 PM John Fox <jfox using mcmaster.ca> wrote:

> Dear Elliot and Ben,
>
> Yes, something definitely seems wrong here, and as usual a reproducible
> example would help. Given that, and as soon as I have some time, I'll
> try to see what went wrong, but I won't be able to do that this week.
>
> My apologies for the problem,
>   John
>
> John Fox, Professor Emeritus
> McMaster University
> Hamilton, Ontario, Canada
> web: https://socialsciences.mcmaster.ca/jfox/
>
> On 2023-01-11 1:12 p.m., Ben Bolker wrote:
> >       The difference in 'Df' between the two components, which appear to
> > have the same fixed-effect model specification, is definitely surprising.
> >
> >       It's not surprising that chisq=9.46 with 2 df could have a lower
> > p-value than chisq=9.89 with 3 df; the larger the df (i.e. the larger
> > the difference in the number of parameters/complexity between the two
> > models implicitly being compared), the more dispersed the null
> > distribution of the deviance difference (=='chisq').
> >
> >     To troubleshoot I would look at the guts of glmmTMB:::Anova.glmmTMB
> > and see what's going on. I'm not claiming that will be obvious: if you
> > can post a *reproducible* example to the glmmTMB issues list I'd be
> > happy to take a look.
> >
> > On 2023-01-11 12:14 PM, Elliot Johnston wrote:
> >> Hi all,
> >>
> >> I am using the car package to run ANOVAs (type II Wald chi square
> >> tests) on
> >> the following model:
> >>
> >> m1 <- glmmTMB(Count ~ Time_Period*Assignment + (1|Region/Site_ID),
> >>                    ziformula = ~ Time_Period*Assignment +
> >> (1|Region/Site_ID),
> >>                    data = allbirds, family = poisson)
> >>
> >> Time Period has three levels and Assignment has two levels. When running
> >> the ANOVA on the conditional component -- car::Anova(m1, component =
> >> "cond") -- the degrees of freedom in the output is as I would expected
> >> (n-1):
> >>
> >>                                  Chisq    Df  Pr(>Chisq)
> >> Time_Period            0.9105  2    0.63429
> >> Assignment             2.1043  1    0.14689
> >> Time_Period:Assignment 6.8486  2    0.03257 *
> >>
> >> But when I run the ANOVA for the zero-inflated component --
> >> car::Anova(m1,
> >> component = "zi") -- the output looks strange:
> >>
> >>                                  Chisq    Df Pr(>Chisq)
> >> Time_Period            9.8876  3   0.019546 *
> >> Assignment             9.4648  2   0.008805 **
> >> Time_Period:Assignment 7.9605  2   0.018681 *
> >>
> >> Why would the degrees of freedom change? FWIW this df discrepancy
> between
> >> the conditional and ZI ANOVAs does *not* happen when running the above
> >> glmmTMB model with subsetted data frames based on different bird
> >> guilds. It
> >> also seems strange that between the Time Period and Assignment terms the
> >> smaller chi square value leads to greater statistical significance. Do
> >> you
> >> agree that something seems wrong here or am I misunderstanding what is
> >> going on under the hood? Any ideas on how to troubleshoot?
> >>
> >> Thank you!
> >>
> >> -Elliot
> >>
> >>     [[alternative HTML version deleted]]
> >>
> >> _______________________________________________
> >> R-sig-mixed-models using r-project.org mailing list
> >> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> >
> > _______________________________________________
> > R-sig-mixed-models using r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>

	[[alternative HTML version deleted]]