Suggested diagnostics for influence on the estimated regression coefficients in a generalized linear model have generally approximated the effect of deleting a single case. We apply the local influence method of Cook (1986) to assess the effect of small perturbations of the data, including the vector of responses, case weights, explanatory variables, and the components of one case. The resulting diagnostics allow one to check for different kinds of influence, and may give insight into its workings. Two examples illustrate some of the diagnostics.
Bibliographical noteFunding Information:
Much of this paper is taken from the first author's Ph.D. thesis, written under the supervision of the second author at the University of Minnesota. This work was supported in part by grants from the National Science Foundation.
Copyright 2010 Elsevier B.V., All rights reserved.
- Data perturbation
- Local influence