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Modeling when all variables are categoricalb

Manuel Spínola 
Dear list memebers,

I am modeling a binary response variable and 6 explanatory factors (all 
my variables, response and explanatory, are categoricals).
I fitted a logistic regression but when I tried to use the CVbinary 
(DAAG package) function to measure the predictive accuracy of the 
regression model with a binary response I got the following result:

 > mod1 = glm(condicion ~ ., family=binomial, data=reglog)
 > CVbinary(mod1)

Fold:  2 1 7 9 6 4 10 5 8 3
Internal estimate of accuracy = NA
Cross-validation estimate of accuracy = NA

Am I getting this result because I am working with a saturated model?
How is the way to model this type of data (1 categorical response 
variable and 6 explanatory factors)?
I also used classification trees for the data but the error is bigger 
after the first split.

Best,

Manuel