I am fitting GLMM's (using a binary variable as response variable and continuous variables as explanatory variables [family = binomial(link="logit")]), and I am interested in obtaining the effect sizes for each explanatory variable.
I obtain the effect size value by calculating odds ratios (Effect size in GLMM).
However, I am considering a variable with a linear (a) and quadratic form(a^2). Here is an example of a model:
model <- x ~ a + I(a^2) + (1|b)
In this case (linear and quadratic forms), 1) is the effect size estimated in the same way (odds ratio), and 2) with the same interpretation?
I can't seem to find information about this topic; do you know of any good literature?