Regression Modeling Strategies With Applications to Linear Models, L
This highly anticipated second edition features new chapters and sections, 225 new references, and comprehensive R software. In keeping with the previous edition, this book is about the art and science of data analysis and predictive modeling, which entai
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Frank E. Harrell, Jr.
Regression Modeling Strategies With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis Second Edition
Springer Series in Statistics Advisors: P. Bickel, P. Diggle, S.E. Feinberg, U. Gather, I. Olkin, S. Zeger
More information about this series at http://www.springer.com/series/692
Frank E. Harrell, Jr.
Regression Modeling Strategies With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis Second Edition
123
Frank E. Harrell, Jr. Department of Biostatistics School of Medicine Vanderbilt University Nashville, TN, USA
ISSN 0172-7397 Springer Series in Statistics ISBN 978-3-319-19424-0 DOI 10.1007/978-3-319-19425-7
ISSN 2197-568X (electronic) ISBN 978-3-319-19425-7 (eBook)
Library of Congress Control Number: 2015942921 Springer Cham Heidelberg New York Dordrecht London © Springer Science+Business Media New York 2001 © Springer International Publishing Switzerland 2015 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 Springer International Publishing AG Switzerland is part of Springer Science+Business Media (www. springer.com)
To the memories of Frank E. Harrell, Sr., Richard Jackson, L. Richard Smith, John Burdeshaw, and Todd Nick, and with appreciation to Liana and Charlotte Harrell, two high school math teachers: Carolyn Wailes (n´ee Gaston) and Floyd Christian, two college professors: David Hurst (who advised me to choose the field of biostatistics) and Doug Stocks, and my graduate advisor P. K. Sen.
Preface
There are many books that are excellent sources of knowledge about individual statistical tools (survival models, general linear models, etc.), but the art of data analysis is about choosing and using multiple tools. In the words of Chatfield [100, p. 420] “. . . students typically know the technical details of regression for example, but not necessarily when and how to apply it. This argues the need for a better balance in the literature and i
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