Re: st: RE: How to "reverse" log transformated result

[Svendsgaard.David@epamail.epa.gov]

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


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