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st: Re: Median survival times via Poisson model, using -margins- ?


From   graupel75@gmail.com
To   Statalist <statalist@hsphsun2.harvard.edu>
Subject   st: Re: Median survival times via Poisson model, using -margins- ?
Date   Tue, 26 Mar 2013 22:46:25 +0800

Austin Nicols writes:

Why not:

use http://www.pauldickman.com/survival/diet, clear
gen t=dox - doe
stset t
stci if hieng==1, by(job)

? Do your example data not represent what you actually have?

Thank you for the suggestion; I should have been more clear! I am
looking to produce covariate-adjusted predictions for a hypothetical
population, and not simple medians from subsamples of my data, hence
the convoluted route. Flex parametric models via  -stpm2- (from ssc)
was the first step, but I am looking to complement that using Poisson
models if possible.

On Tue, Mar 26, 2013 at 11:42 AM,  <graupel75@gmail.com> wrote:
> Apologies, the correct equations and source:
>
> We computed mu as the unweighted average of these 18 death rates [Per
> categorical from Poisson model]. The risk of death at time t, R(t),
> was computed as R(t) = 1 - e ^ (-mu*t), where t was in years. Median
> survival was computed by finding the value of t satisfying the
> relation, R(t) = 1 - e ^(-mu * t) = 0.5.
>
> (from Robbins AS, Whittemore AS, Van Den Eeden SK. Race, prostate
> cancer survival, and membership in a large health maintenance
> organization. Journal of the National Cancer Institute.
> 1998;90(13):986–90.)
>
>
> cheers-
> Andrew Lover
> ______________________________________________
> Epidemiologist
> Centre for Infectious Disease Epidemiology Research (CIDER)
> Saw Swee Hock School of Public Health
> National University of Singapore

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