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

[Magdalena Wiedermann]

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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