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From |
"roland andersson" <rolandersson@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Interpretation of regressionmodel of ln-transformed variable |

Date |
Thu, 6 Nov 2008 08:00:28 +0100 |

There are a total of 303 of 37736 patients with LOS=0. I looked for the different means in the two groups. Obviously the difference is largest for the arithmetic means and almost absent for the harmonic. Can you give an advice on what mean to use when reporting on LOS? -> lapscopiintention = 0 Variable Type Obs Mean [95% Conf. Interval] vtid Arithmetic 28808 2.985178 2.924702 3.045654 Geometric 28586 2.322214 2.304817 2.339742 Harmonic 28586 1.931199 1.918483 1.944085 -> lapscopiintention = 1 Variable Type Obs Mean [95% Conf. Interval] vtid Arithmetic 8928 2.792451 2.745438 2.839463 Geometric 8847 2.294519 2.26541 2.324002 Harmonic 8847 1.933647 1.911211 1.956615 2008/11/5 Maarten buis <maartenbuis@yahoo.co.uk>: > --- "Lachenbruch, Peter" <Peter.Lachenbruch@oregonstate.edu> wrote: >> You can expect differences since your model transforms the response >> variable, while the glm transforms the mean function. The model you >> cite below fits log(mu)=XB, while your other model fit >> E(log(y))=XB. For non-linear functions these won't be the same. > > To expand a bit on that, there are two reasons why the models give > different answers: > > 1) In case of the log transformed y, -regress- with the -eform()- > option will give you a model for the geometric mean, while -glm- with > the -link(log)- option will give you a model of the arithmetic mean. > The two are different but the results should in most cases be pretty > close. > > 2) -regress- with log transformed y will ignore all observations with > an y equal to 0. The reason is that ln(0) is not defined so will give > you a missing value. -glm- models the average y, and an average of 0 is > perfectly legal, so -glm- can handle a LOS of 0 without problem. This > could lead to larger differences between the two models. If you have > observations whose value on the dependent variable is 0, than -glm- is > the preferred method. > > Hope this helps, > Maarten > > ----------------------------------------- > Maarten L. Buis > Department of Social Research Methodology > Vrije Universiteit Amsterdam > Boelelaan 1081 > 1081 HV Amsterdam > The Netherlands > > visiting address: > Buitenveldertselaan 3 (Metropolitan), room N515 > > +31 20 5986715 > > http://home.fsw.vu.nl/m.buis/ > ----------------------------------------- > > > > * > * 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: Interpretation of regressionmodel of ln-transformed variable***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**References**:**RE: st: Interpretation of regressionmodel of ln-transformed variable***From:*"Lachenbruch, Peter" <Peter.Lachenbruch@oregonstate.edu>

**RE: st: Interpretation of regressionmodel of ln-transformed variable***From:*Maarten buis <maartenbuis@yahoo.co.uk>

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