Re: st: Correction for bias in regression estimates after log transformation

[Richard Goldstein <richgold@ix.netcom.com>]

I thank Nick for mentioning my old program; note however, that the 
program offers a choice between smearing and what I call the naive 
estimator (treating the result as lognormal) -- see the article for more 
on this

my preference these days is generally to use glm with the appropriate 
link (which might, or might not, be the log link)

Rich

Nick Cox wrote:
> The issue as I understand it for response y arises because the mean of
> log(y) differs from the log of mean(y). What you do to the predictors is
> immaterial. The problem is generic to any nonlinear transformation. 
>
> I see there being two main relatively simple ways of tackling this
> problem. (There are other more complicated methods; my experience, such
> as it is, indicates that they don't give very different results except
> when results are highly dubious anyway.) 
>
> 1. Avoid it altogether by using -glm- with appropriate link. 
>
> 2. Use smearing. 
>
> Richard Goldstein implemented -predlog- in 1996, which includes
> smearing. 
>
> STB-29  sg48  .  Predictions in the original metric for log-transformed
> models
>         (help predlog if installed) . . . . . . . . . . . . . . . R.
> Goldstein
>         1/96    pp.27--29; STB Reprints Vol 5, pp.145--147
>         calculates three different retransformations, which allow
>         obtaining predictions in the original metric
>
> Both the software and the original article are accessible to all. 
*
*   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/