I am using the function lmer of the library(lme4) to do a GLMM



All models with random intercept works successfully with all my factors.

M4 <- lmer (Stages2 ~ factor(Temperatura) * factor (Sal) *
factor(Food)*factor(Embrion) + (1 | fFemale/fEmbrion), data = PS, family =
binomial)



A model with a random intercept and slope using only one fixed factor in
the random part works successfully Example:
M4 <- lmer (Stages2 ~ factor(Temperatura) * factor (Sal) *
factor(Food)*factor(Embrion) + (1 + factor(Temperatura) |
fFemale/fEmbrion), data = PS, family = binomial)

but when I include in the random part several factors M4 ........... +(1 +
factor(Temperatura) +factor(Food) + factor (Sal)|
fFemale/fEmbrion)........., it
doesn't work.

#Warning message:In mer_finalize(ans, verbose) :
# function evaluation limit reached without convergence (9)



if I use the function lme of the library nlme

the message of R is:

# Error in lme.formula(Stages2 ~ fTemperatura * fSal * fFood * fEmbrion, :
nlminb problem, convergence error code = 1 message = iteration limit reached
without convergence (9)
I want to test if the relationship between the variable Y and fixed
factors is different in each Female. For this reason I need to include
in the random part all the fixed factors.

I think my main problem is that I don't know how can I include 3 factors
in a random intercept and slope model.

All my explanatory variables are factors I mean categoric variables, the
matrix has only 0 and
1. I am using a binomial.

If you know how can I write in R for one of this library the code, it
would be OK for me
thanks in advance.
Enrique
-- 
Gonzalez,Enrique

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