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From |
Mikkel Brabrand <mikkel@brabrand.net> |

To |
"statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |

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

Date |
Sun, 15 May 2011 17:23:44 +0200 |

If I want clinicians to use my model, it needs to be simple. I cannot expect them to use a piece of software to calculate the risk score and it is virtually impossible to have it incorporated in the programs used at my department. I therefore need to simplify it and make the variables categorized or dichotomous. I have previously used the trial and error way, and come up with a model that seems reasonable (and tested it in an independent cohort, and am now testing it in two external cohorts at other hospitals). However, there must be a correct way to select the cuf-off levels, I just cannot find out how. I have asked most statisticians I have met on my way, but no one seems to know how. I hoped that some of you might have a suggestion... Mikkel Den 15/05/2011 kl. 16.49 skrev Nick Cox: > 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/ * * 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:*Nick Cox <njcoxstata@gmail.com>

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

**Re: st: Simplification of formula in logistic regression***From:*Nick Cox <njcoxstata@gmail.com>

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