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Re: st: how to deal with censoring at zero (a lot of zeroes) fora laboratory re
Op 06/08/2005 05:48 PM schreef Maarten Buis:
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.
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
Both points are made in one of those convenient little green sage booklets:
Paul Allison (2002) Missing Data. Tousand Oaks, Sage.
Hope this helps,
Met vriendelijke groet,
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