R: st: R: compare median survival times? (flag: Stata 9.2/SE)

["Carlo Lazzaro" <carlo.lazzaro@tiscalinet.it>]

Marty wrote:
"I'm not familiar with interval quantile regression, but will look into
it..."

Marty may want to take a look at: Koenker R. Quantile Regression. Cambridge
University Press, 2005: 250-255 (particularly).

HTH and Kind Regards,
Carlo
-----Messaggio originale-----
Da: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Martin X
Inviato: venerdì 11 giugno 2010 16.48
A: statalist@hsphsun2.harvard.edu
Oggetto: Re: st: R: compare median survival times? (flag: Stata 9.2/SE)

Thanks for your input, Carlo and Ronan. I agree with Ronan that the code
below will only compare survival functions with defined median survival
times. The hypothesis itself is motivated by my desire to be able to say
that half of group A survived 30 months and half of group B survived
20 months, and the 10 month difference between A and B is statistically
significant. I've already used cox reg to compare the survival functions
(and logistic reg to compare survival at a given time endpoint). Now, I just
want to be able to provide some "common language" results (i.e. months of
survival for half the group).    

Any other thoughts on this? I'm not familiar with interval quantile
regression, but will look into it...

Thanks,
Marty



----- Original Message ----
From: Ronan Conroy <rconroy@rcsi.ie>
To: "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Sent: Fri, June 11, 2010 7:23:28 AM
Subject: Re: st: R: compare median survival times? (flag: Stata 9.2/SE)

On 11 Meith 2010, at 08:44, Carlo Lazzaro wrote:

> Marty may want to customize what follows:
> --------- code begins-----------
> sysuse cancer.dta, clear
> stset studytime, failure(died==1)
> sts test drug if r(p50), logrank
> -------- code ends---------------

But doesn't this just compare the survival function in those in whom the
median survival time is definable?

The hypothesis is a very peculiar one indeed: specifically, that the 50th
percentile of the survival function differs between two groups. I don't know
why anyone would formulate this hypothesis (why the 50th centile and not
some other quantile? why ignore differences at other quantiles?) but it's a
tricky one to try to test. It seems to me that you would need interval
quantile regression, something whose complexities cause one to have to sit
down and drink a glass of water.

Or am I missing something?


Ronan Conroy
=================================

rconroy@rcsi.ie
Royal College of Surgeons in Ireland
Epidemiology Department,
Beaux Lane House, Dublin 2, Ireland
+353 (0)1 402 2431
+353 (0)87 799 97 95
+353 (0)1 402 2764 (Fax - remember them?)
http://rcsi.academia.edu/RonanConroy

P    Before printing, think about the environment




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