The area's benchmark text, completely revised and updated
In the twenty years since publication of the first edition of The Statistical Analysis of Failure Time Data, researchers have produced a library of material on this constantly evolving area. The theoretical underpinnings of established methods have been strengthened, the scope of application has been extended, and counting process methods and related martingale convergence results have led to precise and general asymptotic results. Addressing graduate students, practitioners, and researchers, Jack Kalbfleisch and Ross Prentice update their classic text with these and other current developments in the second edition of The Statistical Analysis of Failure Time Data.
The authors include exercises and examples in each chapter, tying these sophisticated methods to practical applications. The Second Edition develops the dynamics of multivariate failure time data, extends the present material on Markov and semi Markov formulations, and includes an emphasis on left truncation. The final chapter on special topics and examples of data analysis has been completely revised and updated. Other chapters include:
With its comprehensive survey of the field and resources for students and researchers, The Statistical Analysis of Failure Time Data remains the benchmark text of the area.
Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. The Statistical Analysis of Failure Time Data was among those chosen.
This graduate textbook surveys the statistical models and methods used to analyze failure time data, particularly in biomedical contexts. The authors cover inference in parametric models, the Cox regression model, likelihood construction, the accelerated time model, and multi- variate failure models. The second edition adds a chapter on counting processes, martingales, and the associated asymptotic theory. Annotation c. Book News, Inc., Portland, OR