* 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.
Summary: Nice as a reference.... not so good as a class textbook
Rating: 4
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.
Summary: A welcome and well-written update to a classic in the field.
Rating: 5
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.

 

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