[R-sig-ME] Binomial GLMM - Error (invalid class “mer” object)

[ONKELINX, Thierry]

Hi Robert,

Try to clean up your code. Use the data argument instead of the $ notation. And use glmer instead of lmer for generalized models. Addingspacesmakesyourcodemuchmorereadable

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

Which version of R and lme4 are you using? The output of sessionInfo() can be informative for the developers of lme4.

Best regards,

Thierry

ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium
+ 32 2 525 02 51
+ 32 54 43 61 85
Thierry.Onkelinx op inbo.be
www.inbo.be

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~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data.
~ John Tukey

-----Oorspronkelijk bericht-----
Van: r-sig-mixed-models-bounces op r-project.org [mailto:r-sig-mixed-models-bounces op r-project.org] Namens Robert Schaeffer
Verzonden: woensdag 5 december 2012 22:16
Aan: r-sig-mixed-models op r-project.org
Onderwerp: [R-sig-ME] Binomial GLMM - Error (invalid class “mer” object)

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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