# multicollinearity

- Multicollinearity occurs where there is a high correlation between two or more independent variables in a regression analysis. There is considerable disagreement about the degree of correlation that must exist between independent variables before they are considered to be multicollinear. Extreme multicollinearity (for example a correlation of .70 or higher between two independent variables) has adverse effects on the standard errors of the regression coefficients (and hence on tests of their statistical significance and confidence intervals).

*Dictionary of sociology.
2013.*

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**Multicollinearity**— is a statistical phenomenon in which two or more predictor variables in a multiple regression model are highly correlated. In this situation the coefficient estimates may change erratically in response to small changes in the model or the data.… … Wikipedia**Multicollinearity**— In statistics, the occurrence of several independent variables in a multiple regression model are closely correlated to one another. Multicollinearity can cause strange results when attempting to study how well individual independent variables… … Investment dictionary**multicollinearity**— noun 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. See Also: multicollinear … Wiktionary**multicollinearity**— In multiple regression analysis, a situation in which at least some independent variables in a set are highly correlated with each other. [multi + L. col lineo, to line up together] … Medical dictionary**multicollinearity**— mul·ti·col·lin·ear·i·ty … English syllables**multicollinearity**— noun a case of multiple regression in which the predictor variables are themselves highly correlated • Topics: ↑statistics • Hypernyms: ↑multiple regression, ↑multiple correlation * * * ˌkəˌlinēˈarə̇d.ē, kä noun ( es) … Useful english dictionary**Variance Inflation Factor**— A measure of the amount of multicollinearity in a set of multiple regression variables. The presence of multicollinearity within the set of independent variables can cause a number of problems in the understanding the significance of individual… … Investment dictionary**Linear regression**— Example of simple linear regression, which has one independent variable In statistics, linear regression is an approach to modeling the relationship between a scalar variable y and one or more explanatory variables denoted X. The case of one… … Wikipedia**Variance inflation factor**— In statistics, the variance inflation factor (VIF) is a method of detecting the severity of multicollinearity. More precisely, the VIF is an index which measures how much the variance of a coefficient (square of the standard deviation) is… … Wikipedia**Dummy variable (statistics)**— In statistics and econometrics, particularly in regression analysis, a dummy variable (also known as an indicator variable) is one that takes the values 0 or 1 to indicate the absence or presence of some categorical effect that may be expected to … Wikipedia