For GAMs fitted using mgcv::gam, I think that there's an argument that the
most self consistent comparison would be based on the GCV/UBRE score for
the models, since this has usually been used to select the degree of
smoothness of the GAM model (you can fit the GLM using gam(), so this is
avail
R does not contain a gam() function.
*Two* contributed packages, gam and mgcv, do.
Please do as the posting guide asks and clarify what you are talking
about here.
Your penultimate para is not logical: the tests are _not_ based on maximum
likelihood if ML fitting is not used. However, there ar
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.
A GLM is performed for example:
model1
I have a question about how to compare a GLM with a GAM model using anova
function.
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, fami
