Chow test to compare regression on two groups

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Re: Chow test to compare regression on two groups

Richard Ristow
At 06:57 PM 9/14/2010, Doug wrote:

If X is linear, and Y is linear, how can X*Y be nonlinear?

To look from a different, but related, point of view:

The linear model

Y = a*X + b*Y + c

is independent of coordinate changes. That is, if you replace X by X+z (where Z is a constant); or if you replace X by Y-X; you get the same model. NOT that the coefficients will be the same (they won't), but that it will reach the same set of predicted values.

Now, if you have

Y = a*X + b*Y + c*X*Y + d

then if you change coordinates X'=Y-X, meaning X=Y-X', you get

Y = a*(Y-X) + b*Y + c*(Y-X)*Y + d

The third term becomes c*Y^2 - c*X*Y and the new, equivalent model does have a square term, namely Y^2.

If you're going to include product terms (X*Y) but exclude square terms (Y^2), then the second form of the model is "wrong" -- it includes a squared term. But they're the same model.

If you include all second-order terms when you include any (that is, if you include X^2 and Y^2 when you include X*Y), you do get equivalent models after you change coordinates; that is, the model is coordinate-independent. And that's important, because you rarely have a unique 'right' set of coordinates.
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Re: Chow test to compare regression on two groups

Richard Ristow
In reply to this post by Jose Rocha
At 04:29 PM 9/14/2010, Jose Rocha asked:

>How can I include bonferroni correction?

It's what I wrote: since you're performing six tests, instead of
using p<.05 as the criterion for significance, use p<.05/6<~0.008.

There are other, less conservative corrections for multiple
comparisons, but I refer you to others on the list who know more
about those than I do.

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