[R-sig-ME] glmer vs glmmPQL vs glmmadmb

[Ben Bolker]

  If glmer and glmmADMB agree with each other and disagree with
glmmPQL, I would generally trust the former (Laplace approximation is
better than PQL, esp for binary data).  However, (1) you should also
try Gauss-Hermite quadrature (nAGQ>1) in glmer, and (2) the very large
magnitude of your parameters makes it look like you probably have a
complete-separation problem ...


On Mon, Apr 4, 2016 at 10:53 PM, Magdalena Wiedermann <mwiederm at mtu.edu> wrote:
> Dear List
>
> Quick question: Why is the interaction term usingglmmPQL not
> significant, whereas it is highly significant using glmer and glmmadmb?
>
> Thank you!
> Lena
>
> *_
> Example:_*
>
> resp = resp<-cbind(data$Dead, data$Alive)
>
> m1<-glmer(resp~(treatm+log(Tree))^2+block+(1|plot), family=binomial,
> data = data)
>
> summary(m1)
>
>
> m2<-glmmPQL(resp~(treatm+log(Tree))^2+block, random=~1|plot,
> family=binomial, data=data)
>
> summary(m2)
>
>
> |m3<-|glmmadmb|(||resp||~||(||treatm||+||log(Tree)||)^2||+block,
> random=~1|plot,||||family=||"||binomial||"||, ||data=||data||)|
>
> |summary(m3) |*_Results:_*
>
>  > car::Anova(m1)
> Analysis of Deviance Table (Type II Wald chisquare tests)
>
> Response: resp
>                                    Chisq Df Pr(>Chisq)
> treatm                        82.6249  4     <2e-16 ***
> log(Tree)                  17992.6841  1     <2e-16 ***
> block                          3.6873  5     0.5953
> treatm:log(Tree) 230.6844 4 <2e-16 ***
>
>
>  >car::Anova(m2)
> Analysis of Deviance Table (Type II tests)
>
> Response: resp
>                                  Chisq Df Pr(>Chisq)
> treatm                       114.4015  4     <2e-16 ***
> log(Tree)                    384.7095  1     <2e-16 ***
> block                          1.0899  5     0.9550
> treatm:log(Tree) 2.9839 4 0.5605
>
>  > car::Anova(m3)
> Analysis of Deviance Table (Type II tests)
>
> Response: resp
>                                Df     Chisq Pr(>Chisq)
> treatm                        4   68.7297  4.208e-14 ***
> log(Tree)                     1 1846.9933  < 2.2e-16 ***
> block                         5    3.0464     0.6928
> treatm:log(Tree) 4 117.7358 < 2.2e-16 ***
> Residuals                    734
>
>
> p.s.: this it true for summary(m1,m2,m3) too.
>
>
>
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>
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