Survival Analysis: Techniques for Censored and Truncated Data

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Springer Science & Business Media, May 17, 2006 - Medical - 538 pages
Applied statisticians in many fields frequently analyze time-to-event data. While the statistical tools presented in this book are applicable to data from medicine, biology, public health, epidemiology, engineering, economics and demography, the focus here is on applications of the techniques to biology and medicine. The analysis of survival experiments is complicated by issues of censoring and truncation. The use of counting process methodology has allowed for substantial advances in the statistical theory to account for censoring and truncation in survival experiments. This book makes these complex techniques accessible to applied researchers without the advanced mathematical background. The authors present the essentials of these techniques, as well as classical techniques not based on counting processes, and apply them to data. The second edition contains some new material as well as solutions to the odd-numbered revised exercises. New material consists of a discussion of summary statistics for competing risks probabilities in Chapter 2 and the estimation process for these probabilities in Chapter 4. A new section on tests of the equality of survival curves at a fixed point in time is added in Chapter 7. In Chapter 8 an expanded discussion is presented on how to code covariates and a new section on discretizing a continuous covariate is added. A new section on Lin and Ying's additive hazards regression model is presented in Chapter 10. We now proceed to a general discussion of the usefulness of this book incorporating the new material with that of the first edition.
 

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Contents

Examples of Survival Data
1
Chapter 2Basic Quantities and Models
21
Chapter 3Censoring and Truncation
63
Chapter 4Nonparametric Estimation of Basic Quantities
91
Chapter 5Estimation of Basic Quantities
139
Chapter 6Topics in Univariate Estimation
165
Chapter 7Hypothesis Testing
201
Chapter 8Semiparametric Proportional Hazards Regression
243
Chapter 12Inference for Parametric Regression Models
393
Chapter 13Multivariate Survival Analysis
425
Appendix ANumerical Techniques for Maximization
443
Appendix BLargeSample Tests Based on Likelihood Theory
450
C
462
C
468
Appendix DData on 137 Bone Marrow Transplant Patients
484
Bibliography
515

Chapter 9Refinements of the Semiparametric Proportional
295
Chapter 10Additive Hazards Regression Models
329
Regression Diagnostics
353

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