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INFLUENCE DIAGNOSTICS FOR THE NORMAL LINEAR MODEL WITH CENSORED DATA
Authors:L.A. Weissfeld   H. Schneider
Affiliation:Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.;Department of Quantitative Business Analysis, Louisiana State University, Baton Rouge, Louisiana, USA.
Abstract:Methods of detecting influential observations for the normal model for censored data are proposed. These methods include one-step deletion methods, deletion of observations and the empirical influence function. Emphasis is placed on assessing the impact that a single observation has on the estimation of coefficients of the model. Functions of the coefficients such as the median lifetime are also considered. Results are compared when applied to two sets of data.
Keywords:Censored data    influence function    linear model    one-step methods
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