
Definition of Multicollinearity
1. Noun. A case of multiple regression in which the predictor variables are themselves highly correlated.
Definition of Multicollinearity
1. Noun. (statistics) A phenomenon in which two or more predictor variables in a multiple regression model are highly correlated, so that the coefficient estimates may change erratically in response to small changes in the model or data. ¹
¹ Source: wiktionary.com
Medical Definition of Multicollinearity
1. In multiple regression analysis, a situation in which at least some independent variables in a set are highly correlated with each other. Origin: multi+ L. Collineo, to line up together (05 Mar 2000)
Lexicographical Neighbors of Multicollinearity
Literary usage of Multicollinearity
Below you will find example usage of this term as found in modern and/or classical literature:
1. Handbook on Hedonic Indexes and Quality Adjustments in Price Indexes by Jack E. Triplett (2006)
"Conclusion: sources and consequences of multicollinearity Authors of empirical
hedonic studies have so often reported finding multicollinearity that others ..."
2. Strengthening Policy Analysis: Econometric Tests Using Microcomputer Software by Lawrence James Haddad, Daniel Driscoll (1995)
"multicollinearity exists in virtually every data set but is a problem only when
... The main effects of high multicollinearity are that the variances of the ..."
3. Strategies for Sustainable Land Management in the East African Highlands by J. Pender, Frank Place, S. Ehui (2006)
"Regressions were checked for multicollinearity using variance inflation factor (VIF).
The maximum VIF of any of our explanatory variables was 3.63, ..."
4. Production and Consumption of Foodgrains in India: Implications of by J. S. Sarma, Vasant P. Gandhi (1990)
"A principalcomponents approach, as suggested by Mundlak (1981), was also attempted
to get over the problem of multicollinearity. ..."
5. The Effects on Income Distribution and Nutrition of Alternative Rice Price by Prasarn Trairatvorakul (1984)
"Both autocorrelation and multicollinearity are therefore examined. ... The technique
used to correct for multicollinearity combines the conversion of ..."
6. A Metaanalysis of Rates of Return to Agricultural R&D: Ex Pede Herculem? by Julian M. Alston (2000)
"We would most assuredly run into multicollinearity problems if we tried.
Extreme multicollinearity results in an inability to perform the regression at all. ..."
7. Questions and Answers in Lethal and NonLethal Violence: Proceeding of the edited by Richard L. Block (1994)
"Fisher and Mason (1981) describe a number of possible approaches for obtaining
more efficient estimates in the presence of multicollinearity. ..."
8. Handbook on Hedonic Indexes and Quality Adjustments in Price Indexes by Jack E. Triplett (2006)
"Conclusion: sources and consequences of multicollinearity Authors of empirical
hedonic studies have so often reported finding multicollinearity that others ..."
9. Strengthening Policy Analysis: Econometric Tests Using Microcomputer Software by Lawrence James Haddad, Daniel Driscoll (1995)
"multicollinearity exists in virtually every data set but is a problem only when
... The main effects of high multicollinearity are that the variances of the ..."
10. Strategies for Sustainable Land Management in the East African Highlands by J. Pender, Frank Place, S. Ehui (2006)
"Regressions were checked for multicollinearity using variance inflation factor (VIF).
The maximum VIF of any of our explanatory variables was 3.63, ..."
11. Production and Consumption of Foodgrains in India: Implications of by J. S. Sarma, Vasant P. Gandhi (1990)
"A principalcomponents approach, as suggested by Mundlak (1981), was also attempted
to get over the problem of multicollinearity. ..."
12. The Effects on Income Distribution and Nutrition of Alternative Rice Price by Prasarn Trairatvorakul (1984)
"Both autocorrelation and multicollinearity are therefore examined. ... The technique
used to correct for multicollinearity combines the conversion of ..."
13. A Metaanalysis of Rates of Return to Agricultural R&D: Ex Pede Herculem? by Julian M. Alston (2000)
"We would most assuredly run into multicollinearity problems if we tried.
Extreme multicollinearity results in an inability to perform the regression at all. ..."
14. Questions and Answers in Lethal and NonLethal Violence: Proceeding of the edited by Richard L. Block (1994)
"Fisher and Mason (1981) describe a number of possible approaches for obtaining
more efficient estimates in the presence of multicollinearity. ..."