Hi again.  Perhaps a simple question this time....

I am analysing data with a dependent variable of insect counts, a fixed effect of site and two random effects, day, which is the same set of 10 days for each site, and then transect, which is nested within site (5 each).

I am trying to fit the cross classified model using GLMM in lme4. I have, for potential use, created a second coding of transect with levels 1-5 for site 1 and 6-10 for site2. Likewise, if a groupedData object is necessary, there are als ts1 and ts2 dummy variables, as was necessary in the old lme.....

> str(dat3)
`data.frame': 100 obs. of 7 variables:
$ site : Factor w/ 2 levels "Here","There": 1 1 1 1 1 1 1 1 1 1 ...
$ day : Factor w/ 10 levels "1","2","3","4",..: 1 1 1 1 1 2 2 2 2 2 ...
$ trans : Factor w/ 5 levels "1","2","3","4",..: 1 2 3 4 5 1 2 3 4 5 ...
$ count : int 77 109 81 124 115 84 90 85 130 106 ...
$ trans2: Factor w/ 10 levels "1","2","3","4",..: 1 2 3 4 5 1 2 3 4 5 ...
$ ts1 : Factor w/ 10 levels "Here 1","Here 2",..: 1 2 3 4 5 1 2 3 4 5 ...
$ ts2 : Factor w/ 10 levels "Here 1","Here 2",..: 1 2 3 4 5 1 2 3 4 5 ...


Might someone explain to me how I might reflect the fact that transects are different between sites, while days are not?

#this does not work, though I thought it might be the best way to specify the model.....
> GLMM(count~site,data=dat3,random=list(day=~1,trans=~1|site,family=poisso n)
Error in GLMM(count ~ site, data = dat3, random = list(day = ~1, trans = ~1 | :
subscript out of bounds
In addition: Warning message:
"|" not meaningful for factors in: Ops.factor(1, site)


#This does... but also note the differences in the summary and VarCorr variance components...
>summary(GLMM(count~site,data=dat3,random=list(day=~1,trans2=~1),family= poisson))
Generalized Linear Mixed Model


Family: poisson family with log link
Fixed: count ~ site
Data: dat3
      AIC      BIC   logLik
 103.1494 116.1753 -46.5747

Random effects:
 Groups Name        Variance Std.Dev.
 trans2 (Intercept) 0.073011 0.27020
 day    (Intercept) 0.034373 0.18540
# of obs: 100, groups: trans2, 10; day, 10

Estimated scale (compare to 1)  0.6232135

Fixed effects:
            Estimate Std. Error z value Pr(>|z|)
(Intercept)  4.66280    0.13502  34.534   <2e-16 ***
siteThere   -0.25572    0.17216  -1.485   0.1375
---
Signif. codes:  0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1

Correlation of Fixed Effects:
(Intr)
siteThere -0.636
>VarCorr(GLMM(count~site,data=dat3,random=list(day=~1,trans2=~1),family= poisson))
Groups Name Variance Std.Dev.
trans2 (Intercept) 0.028936 0.17010
day (Intercept) 0.013623 0.11672
Residual 0.396322 0.62954



Many thanks andrew

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