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

From   Austin Nichols <[email protected]>
To   [email protected]
Subject   Re: st: R: How to "reverse" log transformed result
Date   Wed, 28 Sep 2011 08:23:29 -0400

Carlo Lazzaro <[email protected]>:
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
(references given at the end), which is the presentation from which
the blog post
(which Nick pointed to) was spawned.

For those who insist on ignoring good advice, and pursuing the
retransformation, see
findit levpredict
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 <[email protected]> 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,
> Carlo
> -----Messaggio originale-----
> Da: [email protected]
> [mailto:[email protected]] Per conto di Morten Støver
> Inviato: mercoledì 28 settembre 2011 9.41
> A: [email protected]
> 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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