Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10525765 | Statistical Methodology | 2005 | 11 Pages |
Abstract
Various diagnostic statistics have been proposed to help identify cases that markedly affect, or influence, the features of a fitted linear regression model. Once influential cases are found, decisions can be made regarding their worth in the model building process. Since a subject data set may contain both singly influential cases and influential multiple case subsets, the capability to assess the joint influence of cases is needed for a complete analysis. The aim of this work is to briefly review Cook's distance measure for multiple cases, an effective diagnostic for this purpose, and present a method using it to search for influential multiple case subsets. The method is applied in two example analyses by way of a MINITAB Statistical Software macro.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Michael R. Delozier, Steven Orlich,