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RE: st: RE: Interpretation of quadratic terms

From   Richard Williams <>
To   "" <>, "" <>
Subject   RE: st: RE: Interpretation of quadratic terms
Date   Wed, 10 Mar 2010 08:40:46 -0500

At 07:34 AM 3/10/2010, Rodolphe Desbordes wrote:
Dear Rosie, Nick and Roger,

To conclude this thread and summarise the main arguments put forward by Nick, Roger and myself:

A) There can be some good reasons for "pre-emptive centering": a) to avoid computational issues, which are unlikely to arise with modern econometric softwares such as Stata; b) to provide substantive interpretation.

I agree with that, and I may add a sentence like that to my notes in the future! One other thought that I have had though: Suppose you are doing tests for collinearity and you have other variables in the model, so I use something like the -collin- command. Is there an advantage to minimizing the collinearity involving the variables that have the squared term? That is, would doing so make me better able to detect where the collinearity is among other variables? Or would it make no difference?

For example, suppose x1 is highly collinear with other variables. If I have x1^squared in the model, I am thinking I might miss the collinearity because x1 and x1^squared are so highly correlated (unless I have centered x1 first). This is just idle speculation on my part, I haven't fiddled around with it to see.

Richard Williams, Notre Dame Dept of Sociology
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