Re: st: partially retrospective survival analysis

[Steven Samuels <sjhsamuels@earthlink.net>]

Alan, the situation you describe is an example of left-censoring.   
Recall that right censoring at a time T provides information that the  
event time Y >T.  The same applies to left-censoring-- Y<T. This is  
generally handled by parametric models, as the likelihood  
contribution of a left-censored event is F(T),  where F(t) = P(Y<t).   
In Stata, the programs -stpm-  (use the leftvar() option and -intreg-  
(and maybe some others) will do this.  I cannot find a Stata command  
to implement Bruce Turnbull's 1976 nonparametric estimate, but -stpm-  
gives flexible models.

-Steve

 (Turnbull, B.W. (1976) The empirical distribution function with  
arbitrarily grouped, censored and truncated data. J. R. Statist. Soc.  
B, 38, 290-295


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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