Survival Analysis with Long–Term Survivors

The data analytic methods routinely applied in the analysis of recidivism data in criminology have been expanded to include immune individuals. This book describes the theory and methods of incorporating them. The analysis of survival data via a model–fitting paradigm consists of the estimation of the parameters of a hypothesised model and the testing of the hypotheses concerning these parameters. The effects of covariates are assessed by asymptotic analyses. The accuracy and power of the asymptotic results are assessed by simulations of real situations. The authors develop the theoretical results required and exemplify the methodology by analysis of a variety of data sets. Probabilistic tools such as the law of large numbers and the central limit theorem are applied.

Spis treści:
Formulating Tests for the Presence of Immunes and Sufficient Follow–up.
Properties of the Kaplan–Meier Estimator.
Nonparametric Estimation and Testing.
Parametric Models for Single Samples.
The Use of Concomitant Information.
Large Sample Properties of Parametric Models: Single Samples.
Large–Sample Properties of Parametric Models with Covariates.
Further Topics.
References.
Statistical Tables.
Index.

Nota biograficzna:
About the Authors Ross Maller received his PhD from the Australian National University and after many years with CSIRO is currently Associate Professor in the Department of Mathematics, University of Western Australia. Xian Zhou is currently at the Department of Mathematics, University of Western Australia.