Timeline for The logrank test statistic is equivalent to the score of a Cox regression. Is there an advantage of using a logrank test over a Cox regression?

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when toggle format	what		by	license	comment
Nov 26 at 14:14	comment	added	Frank Harrell		I wrote about this in more detail at fharrell.com/post/logrank
Jan 5 at 7:08	comment	added	Frank Harrell		No, that is only a warning and can be completely ignored.
Jan 5 at 3:17	comment	added	Cliff AB		Both our statements are correct: likelihood ratio test is statistical valid in the case of perfect separation...but numerical errors will occur, i.e. survival's `coxph` will throw a warning about failure to converge. You and I may be fine ignoring that warning, but biologists who did not publish a book on regression models may be more cautious ;)
Jan 4 at 7:45	comment	added	Frank Harrell		Beg to differ. Nothing is wrong with the likelihood ratio $\chi^2$ tests in the Cox model if there is perfect separation. And yes you can change weights if not using likelihood-based inference (which is quite a loss) but the estimand becomes impossible to describe.
Jan 3 at 17:11	comment	added	Cliff AB		Two advantages of the log-rank statistic over traditional Cox PH: it can give you a p-value if one of the groups has zero events while Cox PH cannot (perfect separation = unbounded MLE's). Second, if a priori we believe the difference should be heaviest at a certain time, we can upweight that region of time for more power.
Sep 9, 2020 at 19:29	vote	accept	Eli
Sep 9, 2020 at 19:29	comment	added	Eli		Thank you. I was never concerned about those disadvantages, though a reminder is helpful. I thought of log-rank as a barebones Frequentist test when you only had a covariate for treatment assignment. I have been genuinely surprised to see it is equivalent to Cox regression.
Sep 9, 2020 at 18:47	history	answered	Frank Harrell	CC BY-SA 4.0