Description
Book SynopsisThe aim of this book is to suggest and exemplify a systematic methodology for analysing survival data which contains immune, or cured individuals, denoted generically as long-term survivors. Such data occurs in medical and epidemiological applications, where the intention may be to identify whether or not cured or immune individuals are present in a population, perhaps as a result of treatments given; in the analysis of recidivism data in criminology, where the intentions are similar with respect to prisoners released from and possibly returning to prison; and in many other areas where followup data is available on individuals, with the possibility that not all suffer the event under investigation. Both nonparametric and parametric methods are proposed and developed. The effects of covariate information can be assessed via a kind of generalised linear framework in the parametric analyses. The proposed methodologies are supported by asymptotic analyses and simulations of real situations
Trade Review"The book contains an admirable blend of theory and practice beingclearly explained and illustrated with realistic examples ofsurvival analyses from medical and criminological studies."
"...an introduction to the analysis of survival data..." (Quarterlyof Applied Mathematics, Vol. LVIII, No. 4,December 2000)
Table of ContentsFormulating Tests for the Presence of Immunes and SufficientFollow-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.
