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e-Book Survival Analysis with Long-Term Survivors download

e-Book Survival Analysis with Long-Term Survivors download

by Xian Zhou,Ross A. Maller

ISBN: 0471962015
ISBN13: 978-0471962014
Language: English
Publisher: Wiley; 1 edition (December 18, 1996)
Pages: 304
Category: Biological Sciences
Subategory: Math Science

ePub size: 1151 kb
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Rating: 4.2
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Ross A. Maller, Xian Zhou. 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.

Ross A. Xian Zhou is currently at the Department of Mathematics, University of Western Australia.

Book Condition: Like New; Hardcover; Close to new condition; Covers are still glossy with “straight" . covers with title in white lettering; 1996, John Wiley Publishing; 304 pages; "Survival Analysis with Long-Term Survivors," by Ross A. Maller & Xian Zhou.

Book Condition: Like New; Hardcover; Close to new condition; Covers are still glossy with “straight" edge-corners; Unblemished textblock edges; The endpapers and all text pages are bright and unmarked; Binding is tight with a straight spine; This book will be stored and delivered in a sturdy cardboard box with foam padding; Medium Format (. " - . 5" tall); Black an. ISBN: 978-0-470-86636-8 November 2000 304 Pages. Starting at just £187. Starting at just £208.

oceedings{, title {Survival Analysis with Long-Term Survivors}, author {R. A. Maller and Xian Zhou}, year {1996} }. R. Formulating Tests for the Presence of Immunes and Sufficient Follow-up.

Start by marking Survival Analysis with Long-Term Survivors as Want to Read .

Start by marking Survival Analysis with Long-Term Survivors as Want to Read: Want to Read savin. ant to Read.

PDF In terms of competing risks Long-term Mixture Survival Models are widely used for the analysis of individuals who may . have to be treated as immune to a specific cause of failure or to be defined as. long-term survivors.

PDF In terms of competing risks Long-term Mixture Survival Models are widely used for the analysis of individuals who may never experience the considered type of failure. In case of multi- or bivariate cause-specific survival data. different dependence structures can be modeled with different copula functions.

Survival Analysis with Long-Term Survivors. ISBN13 9780471962014. More Books . ABOUT CHEGG. Testing for the presence of immune or cured individuals in censored survival data. Biometrics, 1197-1205, 1995. John Wiley & Sons, 1996. C Klüppelberg, A Lindner, R Maller. Journal of Applied Probability 41 (3), 601-622, 2004. Ruin probabilities and overshoots for general Lévy insurance risk processes. C Klüppelberg, AE Kyprianou, RA Maller. The Annals of Applied Probability 14 (4), 1766-1801, 2004.

I am interested in identifying factors that lead to long-term survival among patients undergoing surgery.

First Online: 29 April 2012. This work studies a proportional hazards model for survival data with long-term survivors, in which covariates are subject to linear measurement error. It is well known that the naive estimators from both partial and full likelihood methods are inconsistent under this measurement error model. For measurement error models, methods of unbiased estimating function and corrected likelihood have been proposed in the literature.

The 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. While these theoretical underpinnings are presented in reasonable rigour and detail, the book is aimed very much at the practitioner who wishes to analyse survival data with (or even without) immunes.
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