Is it possible to directly interact the time variable with another variable in survival analysis? Or is that what a log rank test is for? stata Is it possible to directly interact the time variable with another variable in survival analysis? Or is that what a log rank test is for? Working in Stata and I get this error when I try to interact the time variable with another variable (see screen shot). Other interactions seem to be working.
stset dx_lastcontact_death_years, failure(died) exit (time 11) stcox i.stdcare_or_no  i.raceethnicity#c.dx_lastcontact_death_years i.raceethnicity age i.year_group_div i.sex i.charlson_group i.ins_group i.income_group_16 i.education_group i.

 A: It's possible to have an interaction of time elapsed since time = 0 with a variable in a Cox model. That's, for example, how you can model time-varying coefficient values. But it requires special steps.
What you seem to have done is to create an interaction between the last observation time and a predictor in the model for each case. But the last observation time is an outcome in your data. The time dependence vignette of the R survival package discusses the implication of such an interaction variable:

This variable most definitely breaks the rule about not looking into the future, and one would quickly find the circularity: large values of time appear to predict long survival because long survival leads to large values for time.

This circular logical structure is probably why why your model failed even to converge.
In R you can set up a correct interaction between a function of continuous time since time = 0 (not just the last observation time) and a covariate, via a tt() term in a Cox model. I suspect there is something similar in Stata.
This has nothing directly to do with a log-rank test, which is just a test of whether there are any differences among a set of survival curves.
