I'm modeling a set of outcome data the depends on two parameters:
- time, T
- -100 < A < 100
I've done logistic regression using R with the command:
model <- glm(Outcome ~ A + T, family = "binomial", data = myData)
My expectation (the only thing that makes sense) is that when A < 0, the fit probability should be an increasing function of time approaching 0.5, while when A > 0 it should be a decreasing function of time approaching 0.5.
However, the fit I get is that A < 0, A > 0, and A = 0 all are increasing functions of time. They in fact appear to be the same curve just shifted (ie same "shape").
What am I doing incorrectly? Any suggestions?