[R-sig-ME] clustered data with glmer() and glmmPQL()

[Marsela Alvanopoulou]

Hello,

I'm
​ ​
a master student from
​ ​
Greece. I´m trying to model count data with
​ ​
GLMM (lme4
​ ​
package), using as discrete response variable the number of parasites per
fish and as categorical predictor variable three
​ ​
different species.
​ ​
I'm using as random effect the three different tanks I used and as fixed
the infection level
​​
.
​
​
This is the model I'm running:

mod
​ ​
<-
​ ​
glmer
​ ​
(parasite~species+(1|tank),
​ ​
family=poisson
​​
, data=mydata)

I noticed that the estimate of the intercept does not give the mean of the
first species, so I ran a simple glm model to get the estimate. With
summary() I got the p values that allow me to reject my hypothesis and
continue
​ ​
to the Tukey test. Is it legal to use
​
TukeyHSD(aov(parasite~species, data=mydata))
​ ?
​
​
Finally I tested the assumptions
​ ​
and
​ ​
I found violation of normality and independence.

I also tried MASS package where the assumption of independent residuals was
not violated anymore but the histogram gave me a much more skewed
distribution, but also anova() is not available for QTLs.

mod2 <- glmmPQL (parasite~species, random=~1|tank, family=poisson,
data=mydata)

Thank you in advance for your help.

Maria

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