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RE: st: RE: Ordinal logistic regression
From
Nick Cox <[email protected]>
To
"'[email protected]'" <[email protected]>
Subject
RE: st: RE: Ordinal logistic regression
Date
Thu, 11 Nov 2010 16:20:55 +0000
I sympathise with the idea, but that is a different issue.
If I wanted to forecast floods, I would use river discharge as a response, make quantitative predictions, and then the very last step is to see whether discharge means that the river is above some important threshold. Degrading my data to river discharge = {low, medium, high} at the outset is neither necessary nor helpful.
How does obesity differ?
Nick
[email protected]
Mary E. Mackesy-Amiti
I usually feel the same way about reducing information, but in some
cases the clinically-relevant categories are of greater interest than
the continuum.
On 11/11/2010 9:28 AM, Nick Cox wrote:
> Yes, but that strikes me as just throwing away information.
Amal Khanolkar
> I would like to know if BMI categorised into normal, overweight and obese could be considered as ordinal data and if so if be used as the outcome in 'ordinal logistic regression' with categorical exposures?
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