© 1985 by Biometrika Trust
Influence functions for proportional hazards regression
Department of Statistics, University of British Columbia Vancouver, British Columbia V6T 1W5, Canada
Influence functions for the regression parameters in the proportional hazards model are presented. It is suggested that empirical influence functions, computed for each observation and each covariate, can be useful in an informal way to identify influential observations. This is illustrated on the Stanford heart transplant data and two other examples.
Key Words: Censored data Diagnostic Influence function Influential observation Proportional hazards regression Survival data
![]()
CiteULike
Connotea
Del.icio.us What's this?
This article has been cited by other articles:
![]() |
E. L. Hannan, C. Wu, C. R. Smith, R. S.D. Higgins, R. E. Carlson, A. T. Culliford, J. P. Gold, and R. H. Jones Off-Pump Versus On-Pump Coronary Artery Bypass Graft Surgery: Differences in Short-Term Outcomes and in Long-Term Mortality and Need for Subsequent Revascularization Circulation, September 4, 2007; 116(10): 1145 - 1152. [Abstract] [Full Text] [PDF] |
||||
![]() |
L. Pilote, M. Abrahamowicz, E. Rodrigues, M. J. Eisenberg, and E. Rahme Mortality Rates in Elderly Patients Who Take Different Angiotensin-Converting Enzyme Inhibitors after Acute Myocardial Infarction: A Class Effect? Ann Intern Med, July 20, 2004; 141(2): 102 - 112. [Abstract] [Full Text] [PDF] |
||||

