Hi All,

I'm relatively new to using GLMMs and am attempting to run an analysis, but
have encountered an error that I am not sure how to handle.

Error invalidObject(.Object) : invalid class “mer” object: Slot Zt must by
dims['q']  by dims['n']*dims['s']

I am trying to examine the effect of a treatment on the proportion of
flowers probed per foraging bout in an inflorescence. There are two
different pollinator species and each pollinator individual varied in the
number of bouts performed. The data are structured as follows....

     Bee Plant Flowers           Species Treatment Probes fail

1     1     1      14    Bombus appositus    Nectar      4  10

2     1     2      15    Bombus appositus   Control      2  13

4     1     4      12    Bombus appositus   Control      7    5

6     1     6      15    Bombus appositus    Nectar      2  13

7     1     7      10    Bombus appositus   Control      4    6

12    1    12      15  Bombus appositus   Control    11    4

13    2     1      14   Bombus flavifrons     Nectar    14    0

14    2     2      15   Bombus flavifrons    Control      8    7

15    2     3      15   Bombus flavifrons     Nectar      7    8

16    2     4      12   Bombus flavifrons    Control      4    8

17    2     5      16   Bombus flavifrons     Nectar      4  12

18    2     6      13   Bombus flavifrons    Control      5    8

19    2     8      14   Bombus flavifrons     Nectar      1  13

20    2     8      14   Bombus flavifrons     Nectar      5    9

21    2     9      15   Bombus flavifrons     Nectar      7    8

......

465 36    7      10   Bombus flavifrons     Control     1    9

The model structure is as follows:

glmm1<-lmer(cbind(p$Probes,p$fail)~p$Treatment*p$Species+(1|p$Bee), family=
"binomial")

I included Bee identity as a random term to account for pseudoreplication
and differences amongst Bees in the number of bouts performed. At least, I
think this is the correct way to do so. However, I get the error above and
am not sure how to proceed. Any thoughts or suggestions would be greatly
appreciated.


Cheers,

 Robert Schaeffer

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