Overview
- This edition concerns SPSS's 2023 update for Survival Analysis called Accelerated Failure Time
- It also tests the novel methodology against the traditional Cox regression
- First textbook and tutorial of this novel methodology, both for students and professionals
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Table of contents (23 chapters)
Keywords
About this book
An important novel menu for Survival Analysis entitled Accelerated Failure Time (AFT) models has been published by IBM (international Businesss Machines) in its SPSS statistical software update of 2023. Unlike the traditional Cox regressions that work with hazards, which are the ratio of deaths and non-deaths in a sample, it works with risk of death, which is the proportion of deaths in the same sample. The latter approach may provide better sensitivity of testing, but has been seldom applied, because with computers risks are tricky and hazards because they are odds are fine. This was underscored in 1997 by Keiding and colleague statisticians from Copenhagen University who showed better-sensitive goodness of fit and null-hypothesis tests with AFT than with Cox survival tests.
So far, a controlled study of a representative sample of clinical Kaplan Meier assessments, where the sensitivity of Cox regression is systematically tested against that of AFT modeling, hasnot been accomplished. This edition is the first textbook and tutorial of AFT modeling both for medical and healthcare students and for professionals. Each chapter can be studied as a standalone, and, using, real as well as hypothesized data, it tests the performance of the novel methodology against traditional Cox regressions. Step by step analyses of over 20 data files stored at Supplementary Files at Springer Interlink are included for self-assessment.
We should add that the authors are well qualified in their field. Professor Zwinderman is past-president of the International Society of Biostatistics (2012-2015) and Professor Cleophas is past-president of the American College of Angiology (2000-2002). From their expertise they should be able to make adequate selections of modern data analysis methods for the benefit of physicians, students, and investigators. The authors have been working and publishing together for 25 years and their research can be characterized asa continued effort to demonstrate that clinical data analysis is not mathematics but rather a discipline at the interface of biology and mathematics.
Authors and Affiliations
About the authors
Ton J. Cleophas is internist-clinical pharmacologist at the Department of Medicine Albert Schweitzer Hospital Dordrecht the Netherlands. He is also professor of Statistics and member of the Scientific Committee of the European College of Pharmaceutical Medicine Lyon France. He is particularly interested in machine learning methodologies and published many complete-overview-textbooks of the subject.
Aeilko H. Zwinderman is professor of Statistics and Chair of the Department of Biostatistics and Epidemiology at the University of Amsterdam the Netherlands. His current work focuses on development and validation of multivariable models, particularly in genetic research, and he is a major developer of penalized canonical analysis.
Bibliographic Information
Book Title: Modern Survival Analysis in Clinical Research
Book Subtitle: Cox Regressions Versus Accelerated Failure Time Models
Authors: Ton J. Cleophas, Aeilko H. Zwinderman
DOI: https://doi.org/10.1007/978-3-031-31632-6
Publisher: Springer Cham
eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
Hardcover ISBN: 978-3-031-31631-9Published: 30 May 2023
Softcover ISBN: 978-3-031-31634-0Published: 31 May 2024
eBook ISBN: 978-3-031-31632-6Published: 29 May 2023
Edition Number: 1
Number of Pages: XIV, 224
Number of Illustrations: 1 b/w illustrations