https://communities.sas.com/t5/SAS-Procedures/Median-time-and-or-survival-rate-comparision-in-survival-time/m-p/30994#M7374 What about truncating the data to the time point of interest and comparing the differences of the curves up to that point?<BR /> <BR /> I think that's really what's of interest, ie is the surivival different for the first year, second year, etc...<BR /> <BR /> If you truncate at 12 months your estimate is the same as if you hadn't truncated but information afterwards is censoring/truncation in effect. <BR /> <BR /> Does that make any sense? Fri, 21 Jan 2011 22:54:44 GMT Reeza 2011-01-21T22:54:44Z https://communities.sas.com/t5/SAS-Procedures/Median-time-and-or-survival-rate-comparision-in-survival-time/m-p/30991#M7371 Hello all,<BR /> <BR /> In survival analysis (using, say, Kaplan-Meier curves) how can I do such comparisons between two arms? I know log-rank test, but that test is for comparison of two entire survival curves, not just medial survival time or survival rate at certain time point (say, survival rate at 12 months). Personally I don't think this type of comparison is reasonable, and actually I cannot find such single-point comparison in any survival books or statsitical journals, -- I only see this occasionally in certain poster presentations. However, we are sometimes requested to do this by some physicians (like difference or even 95% C.I. of difference of two 12-month survival rates). Any option(s) in, say, "lifetest"? Any suggestions? Thanks! Tue, 09 Nov 2010 16:37:12 GMT https://communities.sas.com/t5/SAS-Procedures/Median-time-and-or-survival-rate-comparision-in-survival-time/m-p/30991#M7371 deleted_user 2010-11-09T16:37:12Z https://communities.sas.com/t5/SAS-Procedures/Median-time-and-or-survival-rate-comparision-in-survival-time/m-p/30992#M7372 Hi.<BR /> Maybe you should use Wilcoxon-rank-sum-test ,because it is nonparameter statistical method which is robust for any distribution. And log-rank is most powerful only for the survival curves both paralleled.<BR /> <BR /> <BR /> Ksharp Wed, 10 Nov 2010 04:21:37 GMT https://communities.sas.com/t5/SAS-Procedures/Median-time-and-or-survival-rate-comparision-in-survival-time/m-p/30992#M7372 Ksharp 2010-11-10T04:21:37Z https://communities.sas.com/t5/SAS-Procedures/Median-time-and-or-survival-rate-comparision-in-survival-time/m-p/30993#M7373 Logistic regression may do what you want. It will handle the failure at a single point in time. It won't handle censoring.<BR /> <BR /> I agree that a complete survival analysis is more powerful, but there are times when it makes clinical sense to address the outcome at a specific point in time. Message was edited by: Doc@Duke Wed, 10 Nov 2010 13:39:07 GMT https://communities.sas.com/t5/SAS-Procedures/Median-time-and-or-survival-rate-comparision-in-survival-time/m-p/30993#M7373 Doc_Duke 2010-11-10T13:39:07Z https://communities.sas.com/t5/SAS-Procedures/Median-time-and-or-survival-rate-comparision-in-survival-time/m-p/30994#M7374 What about truncating the data to the time point of interest and comparing the differences of the curves up to that point?<BR /> <BR /> I think that's really what's of interest, ie is the surivival different for the first year, second year, etc...<BR /> <BR /> If you truncate at 12 months your estimate is the same as if you hadn't truncated but information afterwards is censoring/truncation in effect. <BR /> <BR /> Does that make any sense? Fri, 21 Jan 2011 22:54:44 GMT https://communities.sas.com/t5/SAS-Procedures/Median-time-and-or-survival-rate-comparision-in-survival-time/m-p/30994#M7374 Reeza 2011-01-21T22:54:44Z