[R-sig-ME] Plot glmm full-average model

[Saâd HANANE]

Hi,

I'm performing a glmm modelling using the following script:

aa=read.table("tac.txt", h=T)
attach(aa)
mod=glmer(p~x1+x2*a +x3*as.factor(y)+x4+x5+x6+(1|id), family=binomial,
data=aa)
model.set <- dredge(mod, rank="AICc")
mo <- subset(model.set, !nested(.))
mo
write.csv2(mo,'moo.csv')
top.models <- get.models(mo, subset = delta <2)
top.models
summary(top.models)
mod1<- model.avg(top.models,revised.var = TRUE, adjusted = TRUE, rank =
"AICc")
mod1
summary(mod1)
pred=predict(mod1, type="response")

I'm wondering if any one can help me to plot the "p" (probability of
presence) according x1, x2*a, and x3*as.factor(y).

bestmod (1) :  x1+ x2*a + x3 * as.factor(y)
bestmod (2) :  x1+ x2*a

Thanks

-- 
Saâd Hanane, PhD
Service d'Écologie, de Biodiversité et de Conservation des Sols
Centre de Recherche Forestière
Chariae Omar Ibn Al Khattab, BP 763, Rabat-Agdal/Maroc.

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