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From | Svendsgaard.David@epamail.epa.gov |
To | statalist@hsphsun2.harvard.edu |
Subject | Re: st: RE: How to "reverse" log transformated result |
Date | Wed, 28 Sep 2011 08:44:08 -0400 |
If you use generalize linear models with a log link, you don't have to back transform. If you use log of the dependent variable in a regression and back transform, you are actually getting estimates for the median and not the mean. This could be important in economics if you are really interested in totals and so you would require the means. So, you could use a multi-level model with a log link in your case. Dave David J Svendsgaard, PhD Biostatistician EPA/ORD/NCEA/RTP, Mail Drop B-243-01 Research Triangle Park, NC 27711 Phone (919) 541-4186 Fax (919) 541-1818 From: "Jesper Lindhardsen" <JESLIN01@geh.regionh.dk> To: <statalist@hsphsun2.harvard.edu> Date: 09/28/2011 07:17 AM Subject: st: RE: How to "reverse" log transformated result Sent by: owner-statalist@hsphsun2.harvard.edu Hi Morten, I may have misunderstood, but as you do not provide your syntax and/or exact regression method, it is hard to know. My guess is that the first result is a ratio from comparing groups, while the other result could be an estimate at the mean values in the two groups. As Nick suggested the rate of being granted a disability pension, may be easier to model. Just my thoughts, Jesper -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [ mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Morten Støver Sent: 28 September 2011 09:41 To: statalist@hsphsun2.harvard.edu Subject: 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/ * * 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/