Timeline for Choosing strata in stratified log-rank test
Current License: CC BY-SA 4.0
4 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Mar 31, 2020 at 15:28 | vote | accept | treskov | ||
| Mar 29, 2020 at 23:11 | comment | added | Tomas Bencomo | For a single variable, log-rank test and Cox model will be equivalent. Deciding whether to adjust for other variables depends on study design. If chemotherapy was randomly assigned, it's fine to only analyze chemotherapy effect. If the data is observational, it's important to adjust for other strong prognostic factors (i.e. stage) that affect survival to make as similar comparisons between groups as possible. So in theory, if the patients are the same except for chemotherapy then log-rank test of chemotherapy would be appropriate, but if there are other differences it would be wise to adjust. | |
| Mar 29, 2020 at 22:07 | comment | added | treskov | Thanks a lot for the reply. You say that with a lot of predictors it is better to use multivariable models because of possible interactions and confounding variables which are hard to detect using just log-rank tests. Moreover, obtained results can be misleading. But what if I want to check relationship between survival and just one specific variable. Let chemo be that variable. Would log-rank test be appropriate for this kind of situation assuming all other predictors have approximately the same number of events in each group and the empirical distribution is also similar between groups? | |
| Mar 29, 2020 at 21:10 | history | answered | Tomas Bencomo | CC BY-SA 4.0 |