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Re: st: Re: Partial R-squares


From   Richard Williams <Richard.A.Williams.5@nd.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Re: Partial R-squares
Date   Wed, 15 Sep 2004 07:40:25 -0500

At 04:08 PM 9/14/2004 -0500, Yulia Marchenko wrote:

The partial R-square (or coefficient of partial determination) measures the
marginal contribution of one explanatory variable when all others are
already included in the model. For example, in the above example only 7.7%
of the variation in mpg is reduced by adding weight to the model when length
is already in the model. However, such interpretation is not valid, for
example, if your explanatory variables are collinear.
Brief discussions of partial and semipartial correlations can be found at

http://www.nd.edu/~rwilliam/stats1/x94.pdf

http://www.nd.edu/~rwilliam/stats1/Semipartials-Stata.pdf

Better still is to read the Cohen and Cohen book that is cited in the notes (the notes use the 1975 version of the book but a newer edition was released in 2002 or 2003.)

This is one of those things I tend to teach "because it is there", i.e. it shows up in computer printouts and some authors may use them but it is not something I find terribly useful myself. It does help to make it clear why adding more variables to a model may produce little change in R^2.

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Richard Williams, Notre Dame Dept of Sociology
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