Dear All,
I am currently working on a prognostic model to predict survival
after transient ischaemic attack and minor stroke, and I have a
problem that I don't know the answer to.
The problem is this: A prognostic model was created a while ago.
One of the clinicians here wanted to know whether the degree of
carotid stenosis would improve the model. However, carotid stenosis
wasn't measured in the original data set.
We have a new data set, with all the original prognostic variables
measured in it, and also carotid stenosis. Whatever method I use,
carotid stenosis does improve the model, so now I have to go back to
the clinician with a new 'improved' model. There seem to be various
methods of tackling this.
1. Completely redo the whole model using a whole new set of variables
(some of the original variables are not related to prognosis in our
data set).
2. Add all the original variables into the model using the new data
set, and let their parameter estimates vary. Then add carotid
stenosis in.
3. Add the original variables in the form of the linear predictor
from the original model. Then add carotid stenosis in. The
parameter estimate for the linear predictor is nowhere near one, so
although the parameter estimates of the original variables are being
kept constant relative to one another, their actual magnitudes change
considerably.
4. Add the original variables in the form of the linear predictor
from the original model, and force its parameter estimate to be equal
to 1 (I don't know how to do this). Then add carotid stenosis in.
5. Do something else that I haven't thought of (any suggestions
welcome).
I would be happiest doing either 1), or 2), but the clinician seems
to think that the parameter estimates in the original model are
somehow sacred and not to be changed.
I'd appreciate any views, ammunition, references, etc. I'll post a
summary.
Thanks,
Steff Lewis
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Dr. Stephanie C. Lewis
Medical Statistician
Bramwell Dott Building
Department of Clinical Neurosciences
Western General Hospital
Crewe Road
EDINBURGH Tel: +44 (0) 131 537 2932
EH4 2XU Fax: +44 (0) 131 332 5150
UK Email: [log in to unmask]
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