Unbalance design in GLMM

Hello!

I am working with GLMM using the binomial family for testing
differences in amphibian malformations that occur in several ponds
located in two different areas.
The random effects are sampled day (samplday) and pond identity
(pondident).The fixed effects are area (studyarea) and species (sp).
Ymat is the response variable.

class(data$pondident)

[1] "factor

class(data$samplday)

[1] "integer"

levels(data$pondident)

[1] "A"     "arro"  "B"     "C"     "campo" "D"     "E"     "F"     "G"
[10] "hum"

levels(data$samplday)

NULL

library(biology)
is.balanced(Ymat~pondident,data=data)

[1] FALSE

is.balanced(Ymat~pondident+samplday,data=data)

[1] FALSE

as you notice, it is an unbalanced design, so When I run the model

GLMM.c<-lmer(Ymat~studyarea+sp+studyarea*sp+(1|samplday/pondident),data=data,family="binomial")

Error: length(f1) == length(f2) is not TRUE
Adem?s: Mensajes de aviso perdidos
1: In pondident:samplday :
  expresi?n num?rica tiene 400 elementos: solo el primero es utilizado
2: In pondident:samplday :
  expresi?n num?rica tiene 400 elementos: solo el primero es utilizado

You can help me? I could not find the solution for unbalanced designs
applied to generalized models

Gracias!
Gabriela

Lic. Mar?a Gabriela Agostini


CIMA. Centro de Investigaciones del Medio Ambiente.

Facultad de Ciencias Exactas. UNLP

47 y 115 s/n (1900) La Plata. Argentina


Conservaci?n de Anfibios en Agroecosistemas

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