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| From | Nick Cox <n.j.cox@durham.ac.uk> |
| To | "'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu> |
| Subject | RE: Re: st: RE: Ordinal logistic regression |
| Date | Mon, 15 Nov 2010 13:19:32 +0000 |
Confusion about pounds and kg or inches and cm gives rise to errors about 2 fold, which should often be obvious on careful checking. If worried about outliers, you could always work on a transformed scale (meaning, transform the variable or use a non-identity link function). Logarithms seem natural for a positive number that is really a ratio. Nick n.j.cox@durham.ac.uk Seed, Paul I tried out the links Neil suggested. As expected, dichotomizing generally lead to a loss of power. However, when it did not, this was due to outliers (in y and x). AS BMI is susceptible to occasional genuine extreme outliers, there is some sort of argument for dichotomizing. [...] False outliers in BMI, due to confusing pounds & kg or inches and cm are another matter... * * 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/