The Cox Model and Its Applications
This book will be of interest to readers active in the fields of survival analysis, genetics, ecology, biology, demography, reliability and quality control. Since Sir David Cox’s pioneering work in 1972, the proportional hazards model has become the most
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Mikhail Nikulin Hong-Dar Isaac Wu
The Cox Model and Its Applications
123
SpringerBriefs in Statistics
More information about this series at http://www.springer.com/series/8921
Mikhail Nikulin Hong-Dar Isaac Wu •
The Cox Model and Its Applications
123
Hong-Dar Isaac Wu National Chung-Hsing University Taichung Taiwan
Mikhail Nikulin Université Bordeaux Segale Bordeaux France
ISSN 2191-544X SpringerBriefs in Statistics ISBN 978-3-662-49331-1 DOI 10.1007/978-3-662-49332-8
ISSN 2191-5458
(electronic)
ISBN 978-3-662-49332-8
(eBook)
Library of Congress Control Number: 2016935392 © The Author(s) 2016 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer-Verlag GmbH Berlin Heidelberg
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Preface
Since Sir David Cox’s pioneering work in 1972, the proportional hazards (PH) model has become the most important model in survival analysis and in related applications. The success of the Cox model stimulated further studies in semiparametric and nonparametric theory, counting process models, study designs in epidemiology, and the development of many other regression models which could be more flexible or reasonable in data analysis. Flexible semiparametric regression models are used increasingly often in carcinogenesis studies to relate lifetime distributions to time-dependent explanatory variables. In addition to classical regression models such as the Cox PH model and the accelerated failure time (AFT) model, alternative models like the linear transformation model, the frailty model, and some varying-effect models are also considered by researchers (Martinussen and Scheike 2006; Scheike 2006; Dabrowska 2005, 2006; Bagdonavičius 1978; Zeng and Lin 2007). In this monograph, we discuss some important parametric models as well as several semiparametric regression models. Several classical examples are reconsidered and analyzed here, including the well-k
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