log link versus log response 2

classic Classic list List threaded Threaded
2 messages Options
Threaded
Open this post in threaded view
|  
Report Content as Inappropriate

log link versus log response 2

Tomas Easdale
Thanks Scott,
 
That response is very useful and it all makes sense now as LOG transforming the response works better for heterocedastic data. But your response also brings me to a second question that has been circulating around. What can/should I do if I want to use my regression to predict responses in the original scale. Exponentiate the errors? That doesn't seem much feasible, is it?
 
Cheers
Tomas
   


        [[alternative HTML version deleted]]

_______________________________________________
R-sig-ecology mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
Threaded
Open this post in threaded view
|  
Report Content as Inappropriate

Re: log link versus log response 2

Thierry Onkelinx
Tomas,

What I would do is calculate the median and a confidence interval in the
transformed space. Since the log transformation is a monotone
transformation it will preserve the order of the values. So the median
stays the median, the 2.5% quantile stays the 2.5% quantile and so on.
But be aware that while in the transformed space the median equals the
mean (= the prediction), this will not hold when you backtransform the
values to the original scale.

HTH,

Thierry

------------------------------------------------------------------------
----
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
methodology and quality assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium
tel. + 32 54/436 185
[hidden email]
www.inbo.be

To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to
say what the experiment died of.
~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of
data.
~ John Tukey

-----Oorspronkelijk bericht-----
Van: [hidden email]
[mailto:[hidden email]] Namens Tomas Easdale
Verzonden: donderdag 24 april 2008 5:24
Aan: [hidden email]
Onderwerp: [R-sig-eco] log link versus log response 2

Thanks Scott,

That response is very useful and it all makes sense now as LOG
transforming the response works better for heterocedastic data. But your
response also brings me to a second question that has been circulating
around. What can/should I do if I want to use my regression to predict
responses in the original scale. Exponentiate the errors? That doesn't
seem much feasible, is it?

Cheers
Tomas
   


        [[alternative HTML version deleted]]

_______________________________________________
R-sig-ecology mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/r-sig-ecology

_______________________________________________
R-sig-ecology mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
Loading...