Collinearity

Abstract

Abstract Collinearity reflects situations in which two or more independent variables are perfectly or nearly perfectly correlated. In the context of multiple regression, collinearity violates an important statistical assumption and results in uninterpretable and biased parameter estimates and inflated standard errors. Regression diagnostics such as variance inflation factor (VIF) and tolerance can help detect collinearity, and several remedies exist for dealing with collinearity‐related problems.

Cite this paper

@article{chen2007collinearity,
  title = {{Collinearity}},
  author = {Chen, Gilad},
  journal = {Wiley eBooks},
  year = {2007},
  doi = {10.1002/9780470061572.eqr217}
}

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