Bookmark and Share

Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.


[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

RE: st: RE: Ordinal logistic regression


From   Nick Cox <n.j.cox@durham.ac.uk>
To   "'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu>
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 
n.j.cox@durham.ac.uk 

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?

*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/


© Copyright 1996–2018 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   Site index