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Re: st: visual guide to variable transformations?


From   Austin Nichols <austinnichols@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: visual guide to variable transformations?
Date   Thu, 7 Jun 2012 16:56:51 -0400

Lloyd Dumont <lloyddumont@yahoo.com>:
Why not? Such advice would be generically incorrect.
You are assuming only a bivariate relationship among continuous variables,
but even in such a restricted setting, linearity and normality are far
from required, and it is unclear how you would discern from
most scatterplots how to get there even if they were indicated.

E.g.

clear all
set seed 1
drawnorm z e, n(1000)
g x=normal(z)
g y=x*exp(e)
lpoly y x
g y2=x+rnormal(exp(e),x)
lpoly y2 x

That said, a review of available -glm- links and
common -nl- specifications might make a good FAQ.

On Thu, Jun 7, 2012 at 3:10 PM, Lloyd Dumont <lloyddumont@yahoo.com> wrote:
> Hello, Stalisters.
>
> Does anyone know of a visual guide to variable transformations?  I have seen many decent verbal exlanations of whether, when, and specifically how to transform variables.  But, is there a single resource that shows which transformation is appropriate when.  For example, something like...
>
> When an indep variable is distributed as it is in Figure 1a and is related to the dep var as shown here in Figure 1b, then you should use the _____ transformation.  Then, the transformed indep variable will be displayed as in Figure 1c (which I imagine will almost always be something like a normal distribution) and the relationship between the transformed variable and the dep var will be as displayed in Figure 1d (which I imagine will almost always be linear).
>
> Of course, it all gets a little more complicated if we start talking about transforming the dep var, though this sort of transformation could also easily be displayed and explained visually.
>
> Does anyone know of such a resource?  If not, why not?
>
> Thank you for your thoughts, as always.  Llloyd Dumont

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