In statistics, leverage is a term used in connection with regression analysis and, in particular, in analyses aimed at identifying those observations which have a large effect on the outcome of fitting regression models.
Leverage points are those observations, if any, made at extreme or outlying values of the independent variables such that the lack of neighbouring observations means that the fitted regression model will pass close to that particular observation.[1]
Modern computer packages for statistical analysis include, as part of their facilities for regression analysis, various quantitative measures for identifying influential observations: among these measures is partial leverage, a measure of how a variable contributes to the leverage of a datum.
See also
- Hat matrix — main diagonal contains leverages of the variables
- Mahalanobis distance — a measure of leverage of a datum
- Outliers — data that may have leverage
References
- ^ Everitt, B.S. (2002) Cambridge Dictionary of Statistics. CUP. ISBN 0-521-81099-x
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