Product Description

* Contains additional discussion and examples on left truncation as well as material on more general censoring and truncation patterns.
* Introduces the martingale and counting process formulation swil lbe in a new chapter.
* Develops multivariate failure time data in a separate chapter and extends the material on Markov and semi Markov formulations.
* Presents new examples and applications of data analysis.

Product Details

• Amazon Sales Rank: #104454 in Books
• Published on: 2002-09-09
• Original language: English
• Number of items: 1
• Binding: Hardcover
• 462 pages

Review
"…provides excellent exposure to the theory." (Journal of Statistical Computation and Simulation, June 2005)

"The book contains a wealth of material and analytic insight…will continue to be an invaluable resource for all researchers and graduate students in the field…for years to come." (Journal of the American Statistical Association, December 2003)

"...researchers in hazard function are likely to find new and valuable information in this book..." (Journal of Mathematical Psychology, Vol. 47 2003)

"Do you work in life statistics or reliability statistics? If so, you probably need this book...it contains everything you have ever wanted to know plus a lot more...the second edition...is a great book—improved, modernized, and comprehensive..." (Technometrics, Vol. 45, No. 3, August 2003)

"A review of the first edition, my first contribution to Short Book Reviews...stated 'This book should become a standard reference in the field.' In view of the undeniable accuracy of that prediction, need I say more?" (Short Book Reviews, Vol. 23, No. 2, August 2003)

From the Publisher
Synthesizes statistical models and methods for the analysis of failure time or ``survival'' data. Focuses on regression problems with survival data, specifically the estimation of regression coefficients and distributional shape in the presence of shaping. Deals with the theory, applications and extensions of the proportional hazards model. Includes worked examples and problems for solution.

From the Back Cover
The areas 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:

• Inference in Parametric Models and Related Topics
• Relative Risk (Cox) Regression Models
• Competing Risks and Multistate Models
• Modeling and Analysis of Recurrent Event Data
• Analysis of Correlated Failure Time Data

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.

Customer Reviews

Nice as a reference.... not so good as a class textbook
I believe it is a good book that you can use as a reference book but definitely not as good for a textbook. At many points I feel like the authors are just saying something, and they feel that the reader should believe them, even if they don't justify it.

As class textbooks I like books that give very detailed explanations about everything... because do not forget... Students are people that have their first touch with those materials. Something obvious to the writer... is not obvious to the reader, especially if that student is a student.

If I rate it as a textbook that my professor suggested I will give it low ratings, but since it is not the authors fault if someone suggest this as a textbook then I will see it as a book generally and I will give it 4 stars because it is really good for a reference book.

A welcome and well-written update to a classic in the field.
The prior edition of this book has long been used for introductory courses in survival analysis for statistics students, and its treatment of the proportional hazards model and partial likelihood is classic. Contrary to the claims of another reviewer here, notation for the survival function is far from standardized in the field. In fact, both this book and another standard text ("Analysis of Survival Data" by D.R. Cox and D. Oakes) represent this quantity with an "F". An excellent and authoratative introduction for students with some knowledge of theoretical statistics.

Excellent book on the subject.
Excellent book on the subject. One of the best! The 1st edition has been with me for 20 years. I'm still reading it today. The book is not at the introduction level though. It is at advanced level (grad level for math/stat major).