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Detecting Multicollinearity

Edward R. Mansfield and Billy P. Helms
The American Statistician
Vol. 36, No. 3, Part 1 (Aug., 1982), pp. 158-160
DOI: 10.2307/2683167
Stable URL: http://www.jstor.org/stable/2683167
Page Count: 3
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Detecting Multicollinearity
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Abstract

Multicollinearity may have several adverse effects on estimated coefficients in a multiple regression analysis; consequently, it is important that researchers be trained in detecting its existence. An example is presented that illustrates the need of examining latent roots and latent vectors of the correlation matrix and the variance inflation factors (VIF's).

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