GMMAT model fit and AIC

Question

I have fitted a model using the GMMAT package in R. This model includes several variables and a Genetic Relatedness Matrix to control for the relatedness of the sample.

See this example:

require(GMMAT)
data(example)
attach(example)
model0 <- glmmkin(disease ~ age + sex, data = pheno, kins = GRM, id = "id",
                  family = binomial(link = "logit"))
model0$theta
model0$coefficients
model0$cov


model1 <- glmmkin(disease ~ age , data = pheno, kins = GRM, id = "id",
                  family = binomial(link = "logit"))
model1$theta
model1$coefficients
model1$cov

I would like to fit a full model and then compare restricted models. However, I do not have how to get fit statistics (AIC, R2 and if possible P values) from these models.

The only information I get using summary(model0) is:

> summary(model0)
                  Length Class  Mode   
theta                  2 -none- numeric
n.pheno                1 -none- numeric
n.groups               1 -none- numeric
coefficients           3 -none- numeric
linear.predictors    400 -none- numeric
fitted.values        400 -none- numeric
Y                    400 -none- numeric
X                   1200 -none- numeric
P                 160000 -none- numeric
residuals            400 -none- numeric
scaled.residuals     400 -none- numeric
cov                    9 -none- numeric
Sigma_i                0 -none- NULL   
Sigma_iX               0 -none- NULL   
converged              1 -none- logical
call                   6 -none- call   
id_include           400 -none- numeric

I have tried using:

anova(model0, model1)

but it says:

Error in UseMethod("anova") : 
  no applicable method for 'anova' applied to an object of class "glmmkin"

How can I get fit statistics when using the glmmkin function and compare models? is it possible?

I do not know if I could calculate AIC manually with something like this:

nrow(example$pheno)*(log((sum(model0$residuals^2)/nrow(example$pheno))))+(length(model0$coefficients)*2)

Thank you so much in advance. With all good wishes.