I'm trying to use a Cox proportional hazard model to predict the time until an employee terminates from an organization. There are a bunch of covariates (~20), some of them time-dependent. So I've structured my data appropriately, created a survival object, and fed it to the coxph function successfully. Abbreviated code sample:
surv1 = Surv(Interval.Start, Interval.End, Is.Term.Record) fit1 = coxph(surv1 ~ Age + Tenure + Gender + Stock + Perf, data=mydata)
I have a limited understanding of semi-parametric models and I'm a beginner in R, so I understand the coef and stats output but I don't know how to use
fit1 to make predictions given data on a current employee despite reading some of the other posts on this topic. Should I be using something like
...but in that case, what should
covs look like? And what will the output be--the expected time-to-termination or something else?