Scientific journal paper Q2
New multicollinearity indicators in linear regression models
José Curto (Curto, J. D.); José Pinto (Pinto, J. C.);
Journal Title
International Statistical Review
Year (definitive publication)
2007
Language
English
Country
United Kingdom
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Times Cited: 37

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Abstract
Correlation is an important statistical issue for the Ordinary Least Squares estimates and for data-reduction techniques, such as the Factor and the Principal Components analyses. In this paper we propose new indicators for the multicollinearity problem in the multiple linear regression model.
Acknowledgements
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Keywords
Multiple linear regression,Multicollinearity indicators,Path analysis
Fields of Science and Technology Classification
  • Mathematics - Natural Sciences
Publication Identifiers
ci-pub-10193
2-s2.0-34247224391
WOS:000245604600007
10.1111/j.1751-5823.2007.00007.x
000245604600007
2-s2.0-34247224391
Other Publication Details
2007
Wiley
Web of Science©; Scopus;
0306-7734 (print)
0306-7734 (online)
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75 1
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114 - 121
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