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Model Choice and Influential Cases for Survival Studies
Author(s) -
Wei Wen Hsiang,
Su Ju Shiang
Publication year - 1999
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.1999.01295.x
Subject(s) - mathematics , martingale (probability theory) , regression , statistics , generalization , biometrics , econometrics , regression analysis , computer science , artificial intelligence , mathematical analysis
Summary. Deletion diagnostics are developed for identifying observations that influence the estimates of regression parameters and the mixture parameter in the families of relative risk functions for failure time data. The diagnostic for the regression parameters is a generalization of Cain and Lange's (1984, Biometrics 40 , 493–499) measure of individual influence. The generalizations of martingale residuals, Schoenfeld's partial residuals (1982, Biometrika 69 , 239–241), and score residuals by Therneau, Grambsch, and Fleming (1990, Biometrika 77 , 147–160) are also obtained. The influence of some observations on regression parameters can be drastically modified as the mixture parameter changes, even for a very small change. In addition, adding or deleting some observations might result in choosing different models. The diagnostics are applied to a family proposed by Guerrero and Johnson (1982, Biometrika 69 , 309–314). One illustrative example is presented.