Not sure if this is more of a programming question (in which case please move to stack overflow) or a statistical model question (in which case, please read on!)
I'm exploring a data set and doing cox proportional hazards regression.
One of my variables did not satisfy the proportional hazards assumption so I decided to stratify by that variable.
Stratifying by the variable will assume that the effect of all covariates is the same in each stratum but each stratum has different baseline hazards.
To check this I test for an interaction between the stratifying variable and each covariate. When I run any model with interactions R does something that is unexpected to me:
Call: coxph(formula = Surv(NRM_time, NRM_status) ~ strata(chemosens) + remission + chemosens * (high.LDH + working) + eversmoke + etoh.current + married - chemosens, data = data) coef exp(coef) se(coef) z p remission1 -0.6206 0.538 0.192 -3.225 1.3e-03 high.LDH1 0.8181 2.266 0.177 4.635 3.6e-06 working1 -0.4329 0.649 0.204 -2.121 3.4e-02 eversmoke1 0.1698 1.185 0.125 1.358 1.7e-01 etoh.current1 -0.1633 0.849 0.124 -1.322 1.9e-01 married1 -0.0607 0.941 0.133 -0.455 6.5e-01 high.LDH0:chemosens1 0.8353 2.305 0.255 3.270 1.1e-03 high.LDH1:chemosens1 NA NA 0.000 NA NA working1:chemosens1 0.7644 2.148 0.299 2.553 1.1e-02 Likelihood ratio test=40 on 8 df, p=3.19e-06 n= 738, number of events= 267 (38 observations deleted due to missingness)
As you can see, all my covariates are dichotomous. When I fit the model with interaction between
chemosens and both
working why does R have an interaction term for
high.LDH1 (as opposed to just
high.LDH1 like it did for