I was wondering if the following is a reasonable way to proceed:
I have a number of logistic models, fitted using
glm, that I want to use to make predictions. The models have a continuous variable (call it
cont_var), and for some of the models, a Box-Tidwell test suggests a non-linear relationship between
cont_var and the logit of the outcome.
Should I worry? Here's what I'm thinking:
For any model where there might be non-linearity, I use
splines to fit that model, replacing
ns(cont_var, df = 4). Then, I make the same predictions I made with the original, non-spline model, and see if they give radically different predictions. If not, I conclude that any non-linearity isn't affecting my predictions.
Does that make sense?