- 原书名：Survival Analysis A Self-Learning Text(Second Edition)
- 原出版社： Springer
Chapter I Introduction to Survival Analysis
Abbreviated Outline 2
Detailed Outline 34
Practice Exercises 38
Answers to Practice Exercises 42
Chapter 2 Kaplan-Meier Survival Curves and the
Log-Rank Test 45
Abbreviated Outline 46
Detailed Outline 70
Practice Exercises 73
This second edition has expanded the first edition by adding three new chapters and a revised computer appendix. The
three new chapters are:
Chapter 7. Parametric Survival Models
Chapter 8. Recurrent Event Survival Analysis
Chapter 9. Competing Risks Survival Analysis
Chapter 7 extends survival analysis methods to a class of sur-vival models, called parametric models, in which the distri-bution of the outcome (i.e., the time to event) is specified in terms of unknown parameters. Many such parametric models are acceleration failure time models, which provide an alter-native measure to the hazard ratio called the "acceleration factor". The general form of the likelihood for a parametric model that allows for left, right, or interval censored data is also described. The chapter concludes with an introduction to frailty models.
Chapter 8 considers survival events that may occur more than once over the follow-up time for a given subject. Such events are called "recurrent events". Analysis of such data can be carried out using a Cox PH model with the data layout aug-mented so that each subject has a line of data for each re-current event. A variation of this approach uses a stratified Cox PH model, which stratifies on the order in which recur-rent events occur. The use of "robust variance estimates" are recommended to adjust the variances of estimated model co-efficients for correlation among recurrent events on the same subject.
Chapter 9 considers survival data in which each subject can experience only one of several different types of events ("com-peting risks") over follow-up. Modeling such data can be car-ded out using a Cox model, a parametric survival model or a model which uses cumulative incidence (rather than survival).
The Computer Appendix in the first edition of this text has now been revised and extended to provide step-by-step in-structions for using the computer packages STATA (version 7.0), SAS (version 8.2), and SPSS (version 11.5) to carry out the survival analyses presented in the main text. These com-puter packages are described in separate self-contained sec-tions of the Computer Appendix, with the analysis of the same datasets illustrated in each section. The SPIDA package used in the first edition is no longer active and has therefore been omitted from the appendix and computer output in the main text.
In addition to the above new material, the original six chap-ters have been modified slightly to correct for errata in the first edition, to clarify certain issues, and to add theoretical back-ground, particularly regarding the formulation of the (partial) likelihood functions for the Cox PH (Chapter 3) and extended Cox (Chapter 6) models.
The authors' website for this textbook has the following web-link: http://www, sph.emory, edu/~dkleinb/surv2.htm
This website includes information on how to order this second edition from the publisher and a freely downloadable zip-file containing data-files for examples used in the text-book.
Suggestions for Use
This text was originally intended for self-study, but in the nine
years since the first edition was published, it has also been ef-fectively used as a text in a standard lecture-type classroom format. The text may also be use to supplement material cov-ered in a course or to review previously learned material in a self-instructional course or self-planned learning activity.A more individualized learning program may be particularly suitable to a working professional who does not have the time to participate in a regularly scheduled course.
In working with any chapter, the learner is encouraged first to read the abbreviated outline and the objectives and then work through the presentation. The reader is then encouraged to read the detailed outline for a summary of the presentation,work through the practice exercises, and, finally, complete the test to check what has been learned.
The ideal preparation for this text on survival analysis is a course on quantitative methods in epidemiology and a course in applied multiple regression. Also, knowledge of logistic re-gression, modeling strategies, and maximum likelihood tech-niques is crucial for the material on the Cox and parametric models described in chapters 3-9.
Recommended references on these subjects, with suggested chapter readings are: