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Re: st: how to deal with censoring at zero (a lot of zeroes) fora laboratory re


From   Arnold Kester <arnold.kester@stat.unimaas.nl>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: how to deal with censoring at zero (a lot of zeroes) fora laboratory re
Date   Thu, 09 Jun 2005 11:07:08 +0200

Op 06/08/2005 05:48 PM schreef Maarten Buis:
Arnold kester wrote:


If you want to get a prediction for undetectable Troponin without
assuming a specific value you could add a dummy variable troponin_zero =
(troponin == 0) and substitute (say) zero for log(troponin) when
troponin==0. The predicted value from this model is independent of what
you choose for "log(0)".

Running a regression on an `imputed' missing variables and a dummy variable
to indicate whether a variable was imputed or not will generally lead to biased
estimates.
However, in this case the var is not missing, it is (close to) zero, a valid value. The proposed model supposes a discontinuity in the response between detectable and undetectable.



Both points are made in one of those convenient little green sage booklets: Paul Allison (2002) Missing Data. Tousand Oaks, Sage.

Hope this helps,
Maarten


--
Met vriendelijke groet,
Arnold Kester

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