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Re: st: RE: RE: RE: Ordinal logistic regression
From
Steven Samuels <[email protected]>
To
[email protected]
Subject
Re: st: RE: RE: RE: Ordinal logistic regression
Date
Thu, 11 Nov 2010 13:09:13 -0500
---
And the original height and weight carry even more information. See:
RA Kronmal, 1993. Spurious Correlation and the Fallacy of the Ratio
Standard Revisited. Journal of the Royal Statistical Society A, 156,
379-392.
Steve
[email protected]
On Nov 11, 2010, at 10:53 AM, Nick Cox wrote:
Not at all my meaning; BMI always contains much more information than
any crude categorical reduction of it.
N.B. http://www.stata.com/support/faqs/res/statalist.html#spell
The fact that you have, it seems, categorical predictors is not itself
a reason for categorising the response.
Nick
[email protected]
Amal Khanolkar
Because STATA would create equal intervals between the 3 categories of
BMI?? Would mlogit be a better choice then?
Nick Cox
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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