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From |
"Carlo Lazzaro" <carlo.lazzaro@tin.it> |

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

Subject |
R: st: R: How to "reverse" log transformed result |

Date |
Wed, 28 Sep 2011 18:37:46 +0200 |

Dear Austin, thanks for the guidance. Kindest Regards, Carlo -----Messaggio originale----- Da: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Austin Nichols Inviato: mercoledì 28 settembre 2011 14.23 A: statalist@hsphsun2.harvard.edu Oggetto: Re: st: R: How to "reverse" log transformed result Carlo Lazzaro <carlo.lazzaro@tin.it>: The formula you give relies on very strong assumptions about the error terms, while the -glm- approach does not. This is mentioned elliptically on page 8 ("pernicious retransformation problem") of http://stata.com/meeting/boston10/boston10_nichols.pdf (references given at the end), which is the presentation from which the blog post http://blog.stata.com/2011/08/22/use-poisson-rather-than-regress-tell-a-frie nd/ (which Nick pointed to) was spawned. For those who insist on ignoring good advice, and pursuing the retransformation, see findit levpredict and findit predlog for two options. However, I doubt any of these approaches is a actually a good idea, if the original poster has data where some people have not yet been granted a pension (censored durations), in which case a hazard model is clearly indicated (-help st- in Stata, or -findit hshaz-). It's not clear to me what the value of the multilevel piece is, so I ignore the word, but perhaps the poster can illuminate that value. On Wed, Sep 28, 2011 at 8:04 AM, Carlo Lazzaro <carlo.lazzaro@tin.it> wrote: > > Dear Morten, > I do share the previous comments in that without knowing what you typed is > difficult to advise. > However, for what it worths, back transforming from a log transformation, > the mean on the original scale can be obtained by exp(lm+lv/2), where lm and > lv are the mean and the variance on the log scale, respectively. > > See as a useful reference: Briggs, A. and Nixon, R. and Dixon, S. and > Thompson, S. (2005)Parametric modelling of cost data: some simulation > evidence. Health Economics 14(4):pp. 421-428. > http://eprints.gla.ac.uk/4151/. > > Kindest Regards, > Carlo > > > -----Messaggio originale----- > Da: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Morten Støver > Inviato: mercoledì 28 settembre 2011 9.41 > A: statalist@hsphsun2.harvard.edu > Oggetto: st: How to "reverse" log transformated result > > I'm doing an multilevel linear regression analysis where I try to > investigate if there are variation in the lenght of the rehabilitation > process before people are being granted a disability pension. I measure > this in days, and since my data are very skewed, I've done a log > transformation. Now I wonder how I can transform the results back to the > original scale of measurement. As an example, this are the results for > the different types of diagnosis. > "Other" diagnosis: (ref) > Mental disorders: 0.1993938 > Musulosceletal: 0.0840664 > > If I now try to transform the data back using di exp(.1993938) I get the > result 1.2206626. > If I try to analyse the data without log transforming them, I find that > the mental disorders group have 166 days (95% CI: 75.5-265.6) longer > rehabilitation time before being granted a disability pension than the > "other" diagnosis group. > I guess that the di exp is not the right way to transform the results > back, but I don't know any other way to do it. > I'm using Stata 11. > Thank you for your help * * 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/

**References**:**Re: st: R: How to "reverse" log transformed result***From:*Austin Nichols <austinnichols@gmail.com>

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