In article <[EMAIL PROTECTED]>,
Kelly Smith <[EMAIL PROTECTED]> wrote:
>Hi, I have a model with linear , quadratic and two way interactions. I
>did a step wise regression , eliminated some terms and then did the
>box-cox transformation. Now ,is it possible that after I did the
>box-cox trans, some of the terms that were removed will become
>significant and vice-versa? I'm not sure how to approach it. whether
>to do Box-Cox before step-wise or doing box-cox after stepwise . Your
>insight will be greatly appreciated.
Using a non-linear transformation on data generally destroys
the underlying structure. Regression analysis does not in
any way need normality of data. Models have to come from
knowledge of the subject field, not from data analysis, unless
the fit is really exceptional.
--
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, Dept. of Statistics, Purdue Univ., West Lafayette IN47907-1399
[EMAIL PROTECTED] Phone: (765)494-6054 FAX: (765)494-0558
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