Modeling Discrete Time-to-Event Data
This book focuses on statistical methods for the analysis of discrete failure times. Failure time analysis is one of the most important fields in statistical research, with applications affecting a wide range of disciplines, in particular, demography, eco
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Gerhard Tutz Matthias Schmid
Modeling Discrete Time-to-Event Data
Springer Series in Statistics
Series editors Peter Bickel, CA, USA Peter Diggle, Lancaster, UK Stephen E. Fienberg, Pittsburgh, PA, USA Ursula Gather, Dortmund, Germany Ingram Olkin, Stanford, CA, USA Scott Zeger, Baltimore, MD, USA
More information about this series at http://www.springer.com/series/692
Gerhard Tutz • Matthias Schmid
Modeling Discrete Time-to-Event Data
123
Matthias Schmid University of Bonn Bonn, Germany
Gerhard Tutz LMU Munich Munich, Germany
ISSN 0172-7397 Springer Series in Statistics ISBN 978-3-319-28156-8 DOI 10.1007/978-3-319-28158-2
ISSN 2197-568X (electronic) ISBN 978-3-319-28158-2 (eBook)
Library of Congress Control Number: 2016942538 © Springer International Publishing Switzerland 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 International Publishing AG Switzerland
Preface
In recent years, a large variety of textbooks dealing with time-to-event analysis has been published. Most of these books focus on the statistical analysis of observations in continuous time. In practice, however, one often observes discrete event times— either because of grouping effects or because event times are intrinsically measured on a discrete scale. Statistical methodology for discrete event times has been mainly presented in journal articles and a few book chapters. In this book we introduce basic concepts and give several extensions that allow to model discrete time data adequately. In particular, modeling discrete time-to-event data strongly profits from the smoothing and regularization methods that have been developed in recent decades. The presented approaches include methods that allow to find much more flexible models than in the early times of survival modeling. The book is aimed at applied statisticians, students of statistics and researchers from areas li
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