GLMM glmer and glmmADMB - comparison error - comparison

Question

I am trying to compare if there are differences in the number of obtained seeds in five different populations with different applied treatments, and having maternal plant and paternal plant as random effects. First I tried to fit a glmer model.
dat <-dat [,c(12,7,6,13,8,11)]
dat$parents<-factor(paste(dat$mother,dat$father,sep="_"))
compareTreat <- function(d)
{
d$treatment <-factor(d$treatment)
print (tapply(d$pop,list(d$pop,d$treatment),length))
print(summary(fit<-glmer(seed_no~treatment+(1|pop/mother)+
(1|pop/father),data=d,family="poisson")))
}
Then, I compared two treatments in two populations (pop 64 and pop 121, in that case). The other populations do not have this particular treatments, so I get NA values for those.
compareTreat(subset(dat,treatment%in%c("IE 5x","IE 7x")&pop%in%c(64,121)))
This is the output:
IE 5x IE 7x
10 NA NA
45 NA NA
64 31 27
121 33 28
144 NA NA
Generalized linear mixed model fit by maximum likelihood (Laplace
Approximation) [glmerMod]
Family: poisson ( log )
Formula: seed_no ~ treatment + (1 | pop/mother) + (1 | pop/father)
Data: d
AIC BIC logLik deviance df.resid
592.5 609.2 -290.2 580.5 113
Scaled residuals:
Min 1Q Median 3Q Max
-1.8950 -0.8038 -0.2178 0.4440 1.7991
Random effects:
Groups Name Variance Std.Dev.
father.pop (Intercept) 3.566e-01 5.971e-01
mother.pop (Intercept) 9.456e-01 9.724e-01
pop (Intercept) 1.083e-10 1.041e-05
pop.1 (Intercept) 1.017e-10 1.008e-05
Number of obs: 119, groups: father:pop, 81; mother:pop, 24; pop, 2
Fixed effects:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.74664 0.24916 2.997 0.00273 **
treatmentIE 7x -0.05789 0.17894 -0.324 0.74629
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr)
tretmntIE7x -0.364
It seems there are no differences between treatments. But as there are many zeros in the data, a zero-inflated model would be worthy to try. I tried with glmmabmd, and I wrote the script like this:
compareTreat<-function(d)
{
d$treatment<-factor(d$treatment)
print(tapply(d$pop,list(d$pop,d$treatment), length))
print(summary(fit_zip<-glmmadmb(seed_no~treatment + (1|pop/mother)+
(1|pop/father),data=d,family="poisson", zeroInflation=TRUE)))
}
Then I compared again the treatments. Here I have not changed the code.
compareTreat(subset(dat,treatment%in%c("IE 5x","IE 7x")&pop%in%c(64,121)))
But in that case, the output is
IE 5x IE 7x
10 NA NA
45 NA NA
64 31 27
121 33 28
144 NA NA
Error in pop:father : NA/NaN argument
In addition: Warning messages:
1: In pop:father :
numerical expression has 119 elements: only the first used
2: In pop:father :
numerical expression has 119 elements: only the first used
3: In eval(parse(text = x), data) : NAs introduced by coercion
Called from: eval(parse(text = x), data)
I tried to change everything I came up with, but I still don't know where the problem is.
If I remove the (1|pop/father) from the glmmadmb script, the model runs, but it feels not correct. I wonder if the mistake is in the loop prior to the glmmadmb but it worked OK in the glmer model, or if it is in the comparison itself after the model. I tried as well to remove NAs with na.omit in case that was an issue, but it did not make a difference. Why does the script stop and does not continue running?
I am a student beginner with RStudio, my version is 3.4.2, called Short Summer. If someone with experience could point me in the right direction I would be very grateful!
H.