Re: CLT and regression

In article <1145551418.725578.107440@xxxxxxxxxxxxxxxxxxxxxxxxxxxx>,
Old Mac User <chendrixstats@xxxxxxxx> wrote:
You wrote...

"Any kind of nonlinear transformation will destroy a
putative linear relation. So, no transformations
without an outstanding reason, not involving the data."

I respectively suggest this this makes no sense at all.
If the data (scores) is bounded by 0 - 100... and if you
fit those data without any transformation of the scores
(such as a logistic transformation)... then your finished
model will be capable of predicting outcomes less than
0 and/or greater than 100. That alone is sufficient to
say "use a constraining transformation that will prevent
silly predictions." This is another way of saying that if
you don't do this, your model will not pass the red-face test.

In that case, you should not have considered fitting
a linear relationship at all. I was addressing the one
who changes the form of the relationship to alter the
distribution of the data or the residuals.


--
This address is for information only. I do not claim that these views
are those of the Statistics Department or of Purdue University.
Herman Rubin, Department of Statistics, Purdue University
hrubin@xxxxxxxxxxxxxxx Phone: (765)494-6054 FAX: (765)494-0558
.

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