Timeline for Cox model: using strata() when one comparison group has small N
Current License: CC BY-SA 4.0
6 events
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| Feb 15, 2023 at 15:09 | comment | added | EdM | @hehe the events are all counted in the stratified model, but the covariates of a case having the event are only compared against those still at risk in that stratum when you solve the score equation, not against all at-risk individuals. That might widen the profile of the log-partial-likelihood profiles for the coefficients. Therneau and Grambsch note that loss of precision and power "may be diminished if there are a large number of strata." So your sense that it isn't usually a big problem is correct, with the typical small number of strata. | |
| Feb 15, 2023 at 2:34 | comment | added | hehe | thanks a lot! That makes sense. What is the intuitive reason that many strata will result in reduced precision? since almost all the events will still be counted in the stratified Cox model. | |
| Feb 14, 2023 at 19:02 | comment | added | EdM |
@hehe that would be a problem if there were a group by strata interaction term. Then lack of an event in a group/strata combination can lead to lack of convergence or enormous standard errors of coefficients. Without that interaction, the score equation is based on the sum of log-partial-likelihoods over all strata. See page 45 of Therneau and Grambsch. So, without an interaction between groupand strata, you will still get a coefficient estimate for group provided that each group has an event. The standard error of the estimate might be higher, however, with stratification.
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| Feb 14, 2023 at 18:09 | comment | added | hehe | Will only strata with event in both treatment groups contribute to the effect estimation? That can explain the diminished power. | |
| Apr 10, 2021 at 6:35 | vote | accept | st4co4 | ||
| Apr 9, 2021 at 19:47 | history | answered | EdM | CC BY-SA 4.0 |