[R-sig-ME] Fwd: glmer won't allow quasi- distribution mixed models

Luke Duncan luke@m@ng@li@o@dunc@n @ending from gm@il@com
Mon Jul 9 17:13:27 CEST 2018


Dear R folk

I am trying to run a series of models on distance data for three different
species of animals. My data are not zero-inflated (distances were recorded
for locomotion only and so if the animal didn't move, it wasn't recorded)
and are Poisson distributed. However, all of the models that I run are
horrifically over-dispersed and based on what I read online I thought that
maybe I should consider using a quasi-Poisson distribution to attempt to
account for the over-dispersion. All the online posts of others show that
they do so successfully but for some reason, my lme4 package cannot use
quasi-distributions. I have uninstalled and reinstalled R and the packages
and I still get the same problem.

I am

a) at a loss as to how to deal with the over-dispersion I have and
b) baffled by the fact that lme4 everywhere else can cope with
quasi-distributions but mine can't.

Any help would be appreciated!

My code:

library(lme4)
woodlicedata<-read.csv("Woodlice.csv",header=T)
attach(woodlicedata)
names(woodlicedata)
> ### This set of models examine whether there are differences in distances
travelled.
>
distmodel<-glmer(Distance~Treatment*Sex+(1|ID)+(1|Path.set/ID),family=poisson(link='log'))
> summary(distmodel)  ### AIC= 42972.6
Generalized linear mixed model fit by maximum likelihood (Laplace
Approximation) [
glmerMod]
 Family: poisson  ( log )
Formula: Distance ~ Treatment * Sex + (1 | ID) + (1 | Path.set/ID)

     AIC      BIC   logLik deviance df.resid
 42972.6  43007.3 -21479.3  42958.6     1038

Scaled residuals:
    Min      1Q  Median      3Q     Max
-11.853  -4.074  -1.656   2.146  38.035

Random effects:
 Groups      Name        Variance  Std.Dev.
 ID:Path.set (Intercept) 6.485e-02 0.2546560
 ID          (Intercept) 6.906e-02 0.2627973
 Path.set    (Intercept) 1.368e-10 0.0000117
Number of obs: 1045, groups:  ID:Path.set, 104; ID, 52; Path.set, 2

Fixed effects:
                            Estimate Std. Error z value Pr(>|z|)
(Intercept)                  4.20814    0.07757  54.248  < 2e-16 ***
TreatmentRestricted          0.10843    0.14359   0.755  0.45015
SexMale                     -0.08408    0.11545  -0.728  0.46644
TreatmentRestricted:SexMale -0.49300    0.18781  -2.625  0.00866 **
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Correlation of Fixed Effects:
            (Intr) TrtmnR SexMal
TrtmntRstrc -0.540
SexMale     -0.672  0.363
TrtmntRs:SM  0.413 -0.765 -0.615

>
distmodel2<-glmer(Distance~Treatment*Sex+(1|ID)+(1|Path.set/ID),family=quasipoisson(link='log'))
Error in lme4::glFormula(formula = Distance ~ Treatment * Sex + (1 | ID) +
:
  "quasi" families cannot be used in glmer

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