Reporting Kaplan-Meier / Cox-Proportional Hazard Standard Error, km.coxph.plot, survfit.object
The 10% rule does not provide a unique answer. Should it apply to the cumulative probability, its logarithm, or log-log (log hazard scale)? Many studies are too small to achieve 10% at any time point. I think it is more traditional (but not without bias) to stop where fewer than 10 subjects are still being followed. There's room for many other choices though. Sometimes I think that the curve should go to the max but be accompanied by confidence bands. Frank Paul Johnston wrote
What is the best way to report the standard error when publishing Kaplan-Meier plots? In my field (Vascular Surgery), practitioners loosely refer to the "10% error" cutoff as the point at which to stop drawing the KM curve. I am interpreting this as the *standard error of the cumulative hazard*, although I'm having a difficult time finding some guidelines about this (perhaps I am not searching the correct terms or references). My KM figures contain typically two curves that I am comparing using the logrank test. Inspecting the ?survfit.object yields the std.err field that gives the standard error for each timepoint on the curve. Is it recommended that I just name the timepoint at which the standard error exceeds 0.1 in the figure legend? For example, "The standard error exceeds 10% at time points beyond 394 days." I have seen this strategy in other publications. What is your approach? Thanks for your help, PCJ
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----- Frank Harrell Department of Biostatistics, Vanderbilt University -- View this message in context: http://r.789695.n4.nabble.com/Reporting-Kaplan-Meier-Cox-Proportional-Hazard-Standard-Error-km-coxph-plot-survfit-object-tp4403045p4404200.html Sent from the R help mailing list archive at Nabble.com.