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ammarhm
Lapis Lazuli | Level 10

Hi everyone, 

Could anyone suggest what to do to estimate median (or mean) survival time when less than 50% of observations fail?

One example is to do the following:

 

proc lifetest data=have nelson;
time time*event(0);
run;

This will give the estimated mean (and standard error) survival time

-Is there an easy way to get 95% CI (instead of manually calculating that from SE)

- Is there another or preferred way of getting e3stimated median/ mean survival time? I read that you could use proc lifereg but not sure how to get survival time from that?

Thanks 

1 ACCEPTED SOLUTION

Accepted Solutions
sbxkoenk
SAS Super FREQ

Hello,

 

When not enough events occur, the median can be inestimable.

I seem to remember though that this question was asked before with satisfying answer, but cannot find it anymore.

 

But maybe you can use an alternative measure : RMST .

The restricted mean survival time (RMST), sometimes called the restricted mean event time, is an alternative measure
that is more often reliably estimable than the mean and median of the event time in certain situations. 

 

See this paper :

SAS Global Forum Proceedings -- Paper SAS3013-2019
Analyzing Restricted Mean Survival Time Using SAS/STAT®
Changbin Guo and Yu Liang, SAS Institute Inc., Cary, NC
https://www.sas.com/content/dam/SAS/support/en/sas-global-forum-proceedings/2019/3013-2019.pdf

 

Koen

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1 REPLY 1
sbxkoenk
SAS Super FREQ

Hello,

 

When not enough events occur, the median can be inestimable.

I seem to remember though that this question was asked before with satisfying answer, but cannot find it anymore.

 

But maybe you can use an alternative measure : RMST .

The restricted mean survival time (RMST), sometimes called the restricted mean event time, is an alternative measure
that is more often reliably estimable than the mean and median of the event time in certain situations. 

 

See this paper :

SAS Global Forum Proceedings -- Paper SAS3013-2019
Analyzing Restricted Mean Survival Time Using SAS/STAT®
Changbin Guo and Yu Liang, SAS Institute Inc., Cary, NC
https://www.sas.com/content/dam/SAS/support/en/sas-global-forum-proceedings/2019/3013-2019.pdf

 

Koen

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