On Tue, 26 Oct 2004, SUBIRANA CACHINERO, ISAAC wrote:
I have a question about how to compare a GLM with a GAM model using anova function.
You don't say what gam() function you are using. There are at least two out there and they work in quite different ways.
<snip>A GLM is performed for example:
model1 <-glm(formula = exitus ~ age+gender+diabetes, family = "binomial", na.action = na.exclude)
A second nested model could be:
model2 <-glm(formula = exitus ~ age+gender, family = "binomial", na.action = na.exclude)
Similarly for GAM models
model3 <-gam(formula = exitus ~ s(age)+gender, family = "binomial", na.action = na.exclude)
"R" allows to compare these two models (GLM vs. GAM)
anova(model2,model3, test="F")
This instruction returns a p-value with no error or warning, but this test is based on maximum likelihood, and GAM models are not fitted with maximum likelihood criteria, thus I think this p-value is not correct.
Probably not. If the number of degrees of freedom for age is small it may be quite a good approximation. If you are using mgcv::gam you will have seen a warning to this effect on the help page for anova.gam.
If you need a more accurate test you could simulate from model2 and compare the simulated distribution of the p-value to the value in the observed data.
-thomas
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