Unbalance design in GLMM
Gabriela Agostini <gabrielaagostini18 at ...> writes:
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"
Try making samplday a factor ... In fact, your error is the second one listed under http://glmm.wikidot.com/faq#errors , and making the grouping variables a factor is the suggested remedy.
levels(data$pondident)
[1] "A" "arro" "B" "C" "campo" "D" "E" "F" "G" [10] "hum"
levels(data$samplday)
NULL
[snip] Lack of balance should not be a problem for GLMMs, unless it's extreme (e.g. some completely missing combinations of fixed effects, or all zeros or ones in some random-effect levels, i.e. complete separation). In fact, unbalanced designs are one reason that people use 'modern' mixed models rather than classical method-of-moments ANOVA (which has a hard time with lack of balance).
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")
By the way, studyarea+sp+studyarea*sp is redundant (although harmless). Either studyarea+sp+studyarea:sp (main effects + interaction) or studyarea*sp (ditto, shorthand) should be sufficient
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