A Classification of influence measures

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Abstract
Several influence measures have been developed for evaluating the effects of individual cases on parameter estimates, fitted values, and other least squares regression statistics. Cook and Weisberg (1982), Hocking (1983), and other feel that the average user of regression diagnostics would be overwhelmed and confused by the use of all such diagnostics. However, as Hocking (1983) points out, evidence from which to draw conclusions about the relative merits of existing influence measures in insufficient to make general recommendations about their use. The study provides a complete and systematic graphical exposition of twenty–one existing influence measures. The resulting classification of these measures into five similarity classes greatly simplifies the influence diagnostics menu. Recommendations based on the results of this analysis are made for the use of influence diagnostics.