The Prediction Matrix.
Role of Variables in a Regression Equation.
Effects of an Observation on a Regression Equation.
Assessing the Influence of Multiple Observations.
Joint Impact of a Variable and an Observation.
Assessing the Effect of Errors of Measurements.
A Study of Model Sensitivity by the Generalized Linear Model Approach.
Computational Considerations.
Appendix: Summary of Vector and Matrix Norms, Proofs of Three Theorems.
Refernces.
Index.

SAMPRIT CHATTERJEE, Ph D, is Professor Emeritus of Statistics at New York University. A Fellow of the American Statistical Association, Dr. Chatterjee has been a Fulbright scholar in both Kazhakstan and Mongolia. He is the coauthor of Sensitivity Analysis in Linear Regression and A Casebook for a First Course in Statistics and Data Analysis, both published by Wiley.
ALI S. HADI, Ph D, is a Distinguished University Professor and former vice provost at the American University in Cairo (AUC). He is the founding Director of the Actuarial Science Program at AUC. He is also a Stephen H. Weiss Presidential Fellow and Professor Emeritus at Cornell University. Dr. Hadi is the author of four other books, a Fellow of the American Statistical Association, and an elected Member of the International Statistical Institute.