Dear R-helpers
I have a question related to logistic GAM models. Consider the following
example:
# Load package
library(mgcv)
# Simulation of dataset
n <- 1000
set.seed(0)
age <- rnorm(n, 50, 10)
blood.pressure <- rnorm(n, 120, 15)
cholesterol <- rnorm(n, 200, 25)
sex <- factor(sample(c('female','male'), n,TRUE))
L <- 0.4*(sex=='male') + 0.045*(age-50) + (log(cholesterol -
10)-5.2)*(-2*(sex=='female') + 2*(sex=='male'))
y <- ifelse(runif(n) < plogis(L), 1, 0)
I now want to fit a logistic GAM model and model age as a cubic spline:
fit <- gam(y ~ blood.pressure + sex + cholesterol + s(age, bs="cr")
,family=binomial)
Now my question: In a normal logistic regression, the odds ratio (OR)
simply is the exponentiated coefficient exp(beta).
How is it possible to calculate the odds ratio for age (in this example)
based on the spline? For example the odds ratio based on the spline
between the age of, say, 20-30?
Or even better: How can I plot the odds ratios against age in a continuous
form?
Many thanks for your help.
Best,
Denis Aydin
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