Dear Bert,
you can also translate in nlme, as I'm trying to do, the approach of
Thiébaut and *Gadda( *Mixed models for longitudinal left-censored
repeated measures. Computer Methods and Programs in Biomedicine 74
<http://www.informatik.uni-trier.de/%7Eley/db/journals/cmpb/cmpb74.html#ThiebautJ04>(3):
<javascript:void(0)>(2004)) written in nlmixed(SAS)
Giovanni
Bert Gunter ha scritto:
Dear R Fellow-Travellers:
What is your recommended way of dealing with a left-censored response
(non-detects) in (linear Gaussian) mixed effects models?
Specifics: Response is a numeric positive measurement (of volume, actually);
but when it falls below some unknown and slightly random value (depending on
how the sample is prepared and measured), it cannot be measured and is
recorded as 0.
There is some statistical literature on this, but I was unable to find
anything that appeared to me to implement a strategy in any R package. If it
matters, I am less interested in inference than in removing possible bias in
estimation.
Feel free to respond off-list if you feel that this would not be of general
interest.
Cheers,
Bert Gunter
Genentech
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dr. Giovanni Parrinello
Department of Biotecnologies
Medical Statistics Unit
University of Brescia
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