Bookmark and Share

Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.


[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

Re: st: Relative Importance of predictors in regression


From   David Hoaglin <[email protected]>
To   [email protected]
Subject   Re: st: Relative Importance of predictors in regression
Date   Mon, 4 Nov 2013 17:28:16 -0500

Hi, Sam.

I'm not sure what you mean by "the mathematical expression for 'held
constant,'" other than setting each of the other predictors to some
particular value.

The general interpretation of the coefficient of a predictor in a
multiple regression is that it tells how the dependent variable
changes per unit increase in that predictor, adjusting for
simultaneous linear change in the other predictors in the data at
hand.  If the model has n observations on Y and p predictors
(including the constant, if present), and the data on the predictors
form the columns of the (full-rank) matrix X, the mathematics of
ordinary least squares involves projecting Y on the subspace of
n-space spanned by the columns of X.  Nothing in that process of
projection holds the other predictors constant at particular values.

Regards,

David Hoaglin

On Mon, Nov 4, 2013 at 3:39 PM, Lucas <[email protected]> wrote:
> What would be the mathematical expression for "held constant"? And
> what is the mathematical expression to which you are comparing it that
> leads you to reject "held constant"?
>
> Thanks a bunch!
>
> Sam
*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/faqs/resources/statalist-faq/
*   http://www.ats.ucla.edu/stat/stata/


© Copyright 1996–2018 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   Site index