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Re: st: comparing 25th percentile survival time between two race groups

From   Steve Samuels <>
Subject   Re: st: comparing 25th percentile survival time between two race groups
Date   Fri, 28 Sep 2012 17:26:10 -0400

Dear Haena:
> On Sep 28, 2012, at 2:43 PM, Haena Lee wrote:
> Hi Listers,
> I have tried to produce the median survival time and its 95% CI with
> renal transplant data. "Stci" command, however, did not produce any
> median values. So I generated the graph of median survival time by
> race (African American vs. White) and the graph showed it only reached
> to the length of 25% in the course of follow-up, indicating both of
> groups have died not even near 50% (median), but mostly near the
> length of 25% tile in the course of follow-up.
What you observe can be better phrased as saying that followup was not 
long enough to observe 50% of failures. 

> 1. Given this, I attempted to produce 25th percentile survival time.
> However I am struggling with comparing the difference of 25th
> percentile survival time between African American and White across 10
> regions in US. The command that I used:
> sort UNOS
> by UNOS: stci , by(race_all) p(25)

> I was trying to use "ranksum" but it doesn't have an option for
> testing differences of other percentiles besides median. Which command
> should I use?

That's a correct command. It tests for any difference where survival
in one group is better, not just differences in medians.
> 2. In comparing the median to the 25 percentile, there are some
> regions where the length to 25% tile is significantly longer than
> median. In this case, what would you guys do? If you would choose to
> use median survival time, then what else could I do in order not only
> to produce the median survival time and 95% CI, but to test the
> difference of median survival time between groups instead stci (since
> it didn't produce in previous analysis)?

Your observation is impossible in theory; to persuade us, you'd need to
follow the advice in Statalist FAQ (3.3) and show us the commands and
results that lead you to this observation.

If I had to guess, I'd say that you looked at the Kaplan-Meier survival
curve, not at -stci- results. A survival curve shows the proportion of
people who haven't had the event at a time, not the proportion who have
failed. Thus the point corresponding to the 25% mark on the y axis is where
25% of people haven't failed and 75% have. In other words it is the 75th
percentile for failure. To see the failure time percentiles, the command

sts graph, failure

You might benefit from reading a good text on survival data, e.g. Cleves
et al. (2010).

Reference: Cleves, Mario, William Gould, Roberto Gutierrez, and Yulia
Marchenko. 2010. An Introduction to Survival Analysis Using Stata, Third
Edition. College Station, Tex: Stata Press.


> Thank you so much!
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