"Imagine---a statistics textbook that actually explains things in English instead of explaining a topic by bombarding the reader with page-widthj equations requiring an advanced degree in Math just to read the book. If it weren't for this book, I would be really stuck.„ (David Britz)
From the reviews of the second edition:
“The most meaningful accolade that I can give to this text is that it admirably lives up to its title.„ Journal of the American Statistical Association, September 2006
“This text is … an elementary introduction to survival analysis. It is primarily intended for self-study, but it has also proven useful as a basic text in a standard classroom course … . Each chapter starts with an Introduction, an Abbreviated outline, and Objectives, and ends with self tests, exercises and a detailed outline. Solutions to tests and exercises are also provided." (Göran Broström, Zentralblatt MATH, Vol. 1093 (19), 2006)
This is the second edition of this text on survival analysis, originallypublishedin1996. Asinthe? rstedition, eachch- ter contains a presentation of its topic in “lecture-book” f- mat together with objectives, an outline, key formulae, pr- tice exercises, and a test. The “lecture-book” format has a sequence of illustrations and formulae in the left column of eachpageandascriptintherightcolumn. Thisformatallows youtoreadthescriptinconjunctionwiththeillustrationsand formulae that high-light the main points, formulae, or ex- ples being presented. This second edition has expanded the ? rst 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 s- vival models, called parametric models, in which the dist- bution of the outcome (i. e. , the time to event) is speci? ed intermsofunknownparameters. Manysuchparametricmodels are acceleration failure time models, which provide an alt- 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. Chapter8considerssurvivaleventsthatmayoccurmorethan once over the follow-up time for a given subject. Such events are called “recurrent events”.
