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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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