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st: Re: R: How to "reverse" log transformed result

From   Morten Støver <>
To   Carlo Lazzaro <>
Subject   st: Re: R: How to "reverse" log transformed result
Date   Wed, 28 Sep 2011 14:43:16 +0200

About the multi-level piece: One of the things I will investigate is whether the time of the rehabilitation time varies between the municipalities.
If I "translate" my code it could look something like:
xtmixed logtime gender age unemployment i.diagnosis, || municipality:, var

On 28.09.2011 14:04, Carlo Lazzaro 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.

Kindest Regards,

-----Messaggio originale-----
[] Per conto di Morten Støver
Inviato: mercoledì 28 settembre 2011 9.41
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

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Morten Støver
PhD research fellow
Department of Public Health and General Practice
Norwegian University of Science and Technology
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