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RE: st: partially retrospective survival analysis


From   "Feiveson, Alan H. (JSC-SK311)" <alan.h.feiveson@nasa.gov>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: partially retrospective survival analysis
Date   Wed, 9 Apr 2008 15:44:16 -0500

Hi Steven - Thanks for your thoughts on this. I guess the intent is to
use all the data on hand to develop a survival prediction based on the
same measurements on some future patient. But even with left censoring,
I'm afraid the sample of "zeros" is not random in the sense that those
patients probably wouldn't even have been in the sample if their events
hadn't already occured. However -intreg- is a reasonable try. Thanks for
the suggestion.

Al

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Steven
Samuels
Sent: Wednesday, April 09, 2008 3:33 PM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: partially retrospective survival analysis

Alan, I wanted to add:  I don't know how to predict a prior event from
later data.  So, ECG measurements after the fact seem useless to me.

-Steve
On Apr 9, 2008, at 3:23 PM, Feiveson, Alan H. (JSC-SK311) wrote:

> Hi - Has anyone seen models for or tried doing a survival analysis 
> when for some observations the data had been observed after the event 
> already occurred? For example, trying to predict time to heart attack 
> given some ECG measurements, but for some patients, the measurements 
> were obtained after the patient already had been in the hospital after

> the attack. So in one sense the time to event is actually negative and

> censored at zero. Probably a better approach would be some sort of 
> discrete/continuous mixture model where with a certain probability, 
> the event has already occurred and given that it hasn't, a standard 
> survival model takes effect.
>
> Al Feiveson
>
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