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From |
Nick Cox <njcoxstata@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Simplification of formula in logistic regression |

Date |
Sun, 15 May 2011 15:49:37 +0100 |

I don't know what "statistically correct" would mean here. If you think your model is useful, there are no grounds for coarsening it. If the implication is that clinicians can't understand or don't need to understand the internals of the formula you can think of encapsulating the details in a Stata do-file or some equivalent in other software. A broad issue is that detailed models optimised to fit particular datasets often perform poorly on other data. Nick On Sun, May 15, 2011 at 3:43 PM, Mikkel Brabrand <mikkel@brabrand.net> wrote: > I have performed a logistic regression analysis including five variables and one outcome. However, I would like to simplify the formula significantly for clinical use. So, instead of the formula been something like -12.22+2.33*systolic blood pressure-1.21*temperature etc., I would like to make a scoring system where the score is calculated on basis of the measured values of the vital signs. > > An example could be something like this > > .................2 points..1 point...0 points...1 point.....2 points > > Pulse ...........-30........31-50....51-100....101-200..201- > > Sys. BP.........-60........61-100..101-200...201- > > However, I have no idea how to find the optimal cut-off points. Do any of you have a suggestion how to do this statistically correct? * * 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/

**Follow-Ups**:**Re: st: Simplification of formula in logistic regression***From:*Mikkel Brabrand <mikkel@brabrand.net>

**References**:**st: Simplification of formula in logistic regression***From:*Mikkel Brabrand <mikkel@brabrand.net>

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