Dear all. I am working with a GLMM in the lme4 package using 4 fixed
factors and 1 random factor (plot). An unexpected result comes up when I
calculate the model's conditional and marginal R-squared using the
r.squaredGLMM funtion in the MuMIn package. Both values are the same. Does
this mean the random term does not add any explanatory power to the model
(and could thus be dropped)? I provide a working code below. Thanks in
advance for your help.
Marcos
id <- "0Bzd8I1jr8z_iRm1aRWhqdHJHcmc" # google file ID
comuni <- read.table(sprintf("https://docs.google.com/uc?id=%s&
export=download", id), head=T, sep="")
comuni1<-comuni[-c(3,6,7,8),] #these data points I don't need
library(lme4)
MM1A <- glmer(riquplanta ~width+lot+exph200+db500+(1|plot), data = comuni1,
family=poisson, control=glmerControl(optimizer="bobyqa",
optCtrl=list(maxfun=2e5)))
summary(MM1A)
library(MuMIn)
r.squaredGLMM(MM1A) #what's going on here?
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Bi?l. Marcos Monasterolo
Becario doctoral - C?tedra de Bot?nica General, Facultad de Agronom?a, UBA