High leverage point: another source of multicollinearity. (English) Zbl 1129.62395

Summary: Multicollinearity often causes a huge interpretative problem in linear regressions analysis. There is a large body of literature available about the sources of multicollinearity. In our work we find another important and almost inevitable source of multi-collinearity that is the existence of high leverage points in a linear model. Leverage values play very important role in regressions analysis. They often form the basis of regression diagnostics as measures of influential observations in the explanatory variables. It is generally believed that high leverage points are responsible for causing masking of outliers in linear regression. But we observe that high leverage points may also be responsible for causing multicollinearity. We present few examples and figures, which draw our attention to this problem. Then we investigate the nature and extend of multicollinearity caused by the high leverage points through Monte Carlo simulation experiments.


62J05 Linear regression; mixed models
62J20 Diagnostics, and linear inference and regression