Regress - are the regression coefficient standardized?

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Alwin
Alwin 2012-3-21
Hi
I am conducting a multiple linear regression analysis with the following regress command: [b,bint,r,rint,stats] = regress(y,X) Where b is the coefficient array. When I want to compare the different regression coefficients with each other in order to estimate the influence on the response in y I generally have to standardize the regression coefficients in order to make them comparable. My question is: Are the regression coefficients already standardized when applying the regress command OR do I have to do it manually?
Thank you very much.
  2 个评论
Oleg Komarov
Oleg Komarov 2012-3-21
The second but you can normalize your regressors with zscore.
Alwin
Alwin 2012-3-21
Thanks, Oleg. I normalized the regressors manually using the same equation zscore applies, before I read your comment. Luckily the results conform each other. Another question I have is, if I still have to include the ones columns as a constant (e.g. [ones(size(x1))) when applying regress. I tried both with and without constant and the regression coefficients seem to be the same. So it doesn't matter if I include the constant column, right?

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Oleg Komarov
Oleg Komarov 2012-3-21
No, regress doesn't normalize automatically the regression coefficients.
One workaround is to normalize your regressors with zscore
What about the intercept?
The standardization centers the data around 0 and the regression line should go through the origin. However, in small samples you may still get a significant alpha.
  • big sample: do not include the ones (but double check anyways, alpha should be 0 or non significant).
  • small sample: include the intercept.

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