[R-sig-ME] glmer.nb - interaction interpretation

Fox, John j|ox @end|ng |rom mcm@@ter@c@
Tue Jul 30 22:15:57 CEST 2019


Dear Jorge,

You might try the predictorEffects() function in the effects package to visualize the interaction. In particular, and as a start, plot(predictorEffects(mod)), where mod is the model you wish to examine.

I hope this helps,
 John

-----------------------------------------------------------------
John Fox
Professor Emeritus
McMaster University
Hamilton, Ontario, Canada
Web: https://socialsciences.mcmaster.ca/jfox/



> -----Original Message-----
> From: R-sig-mixed-models [mailto:r-sig-mixed-models-bounces using r-
> project.org] On Behalf Of Cueva, Jorge
> Sent: Tuesday, July 30, 2019 10:34 AM
> To: r-sig-mixed-models using r-project.org
> Subject: [R-sig-ME] glmer.nb - interaction interpretation
> 
> Dear all
> I hope to get support for interpreting a model. First, I am assessing the natural
> regeneration in a dry forest. The design has 12 clusters and each cluster
> includes 3 open and 3 fenced plots (a total of 36 open plots and 36 fenced
> plots), the open plots are separate from the excluded plots by only 20 meters.
> I want to know if livestock grazing affects the abundance of regeneration, for
> this we collected excrements of animals, but a single sample of excrements
> affects both the open and the fence plot.
> 
> Of all the models tested, the best was:
> glmer.nb(Ind ~ 1 + Equine * Treat + SPrec + Cattle + (1|Cluster), data =
> BaseOb2, family=poisson, verbose=FALSE, glmerControl(optimizer="bobyqa",
> optCtrl = list(maxfun = 2e5)))
> 
> Ind = number of individuals
> Equine = weight of equines excrements (horses + donkeys) Treat = treatment
> (open and exclusion plots) SPrec = seasonal precipitation Cattle = weight of
> cattle excrements Cluster = cluster was used as random predictor because the
> samples were nested in the cluster.
> 
> My issue is when I want to interpret the effect of the predictors. Here are the
> results
> 
> Fixed effects:
>                                               Estimate              Std. Error             z value
> Pr(>|z|)
> (Intercept)                          3.170153             0.246584             12.856                  <
> 2e-16 ***
> Equine                                 0.926521             0.233079             3.975
> 7.03e-05 ***
> Treatopen                          -0.009898            0.068965             -0.144
> 0.885875
> SPrec                                    0.390747             0.078133             5.001
> 5.70e-07 ***
> Cattle                                   -0.365988            0.184748             -1.981
> 0.047589 *
> Equine:Treatopen            -0.989678            0.274040             -3.611
> 0.000305 ***
> 
> It can be seen that the independent effect of Equine is significantly positive
> and that of Treatopen non-significantly negative. Interpretation of these
> would be easy, but my issue is the Equine:Treatopen interaction. Why is the
> effect of Equine first positive and then in the interaction negative? What does
> that mean?
> 
> Very grateful in advance.
> 
> Jorge Cueva Ortiz
> PhD Candidate
> Technical University of Munich
> 01631327886
> 
> 
> 	[[alternative HTML version deleted]]
> 
> _______________________________________________
> R-sig-mixed-models using r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models



More information about the R-sig-mixed-models mailing list