Thanks for your thoughts.
1. The function is 'somewhat' linear. Small curvature but beginning and end are
similar. Off course I could fit more complex functions of time.
2. Do I really have to build (start, stop) datasets as I have time-varying
covariate effect but not time-varying covariate?
Dear All,
I have built a survival cox-model, which includes a covariate * time
interaction. (non-proportionality detected)
I am now wondering how could I most easily get survival predictions from my
model.
My model was specified:
coxph(formula = Surv(event_time_mod, event_indicator_mod) ~ Sex +
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