Survival Analysis

Rating:
Summary: A good book of studying Survival Analysis
Review: In this new edition, many errata are corrected and each of the theories has a reason why this is true. Although they may be more practical in view, it is very good to use them to learn Survival Analysis, which is more realistic in sense.

In its Theoretical Notes and Practical Notes, there are a lot of different views and sights to show that which is the best to use. The examples are more or less good one and explained in a more detailed way than that in the 1st edition. A good-buy and must-read for those want to have a thorough view in this aspects. Read them carefully! Better than Cox's in this new edition. Buy and read this new edition!

Rating:
Summary: Good book of Studying Survival Analysis
Review: In this new edition, most of the errata are corrected and the texts are explained in a more detailed way.

The formulae are correct and the examples are explained in a more direct and expressive way than that in the 1st edition.

The most valuable one is its Theoretical Notes and Practical Notes. They show a lot of different points of views.

A good-buy and must-read for those want to have an intense level in Survival Analysis. Suitable for elementary and intermediate candidates to read and study.

Ian Lauder

Rating:
Summary: Graduate Level Text in Survival Analysis
Review: Klein and Moeschberger's Survival Analysis: Techniques for Censored and Truncated Data is a valuable resource for those who use survival analysis in their research or job. Survival analysis is techniques to analyze time to event problems. For example, how long does it take for a released felon to go back to jail. The main point to understand about the book is it's a graduate level text. The authors rely heavily on mathematics and use it to derive the procedures used in survival analysis. One needs a strong background in math, including calculus and linear algebra, and first year graduate level courses in statistics and econometrics to understand the book. If you do not feel comfortable with math or do not have a graduate level background in statistics then this book would be a waste of your time and money. Klein and Moeschberger make extensive use of practical examples to illustrate how the techniques are used. This helped greatly because one might get lost with the math. The other major benefit of the book is it covers a wide range of topics including: censored data, estimation of survival and hazard functions, hypothesis testing, Cox proportional hazards model, additive models, regression diagnostics, parametric models, and multivariate survival analysis. I would recommend you buy a more nontechnical book first, for example Kleinbaum's Survival Analysis or Hosmer and Lemshow's Applied Survival Analysis. These books would provide a more intuitive understanding of survival analysis. Then if you desire a more technical understanding or need to understand topics not covered in the other books then buy Klein and Moeschberger's book.

Rating:
Summary: Worst Textbook Ever
Review: Murphy's Law of College Textbooks: When an author prepares a textbook on a topic he doesn't understand thoroughly, his work will only be understood by those readers who understand more about the topic than the writer . . . thus defeating the prime purpose of writing, which is to inform those who understand less about the topic than the writer.

The above statement applies to this textbook more than to any other that I have ever read in my life. Each chapter reduces to nothing more than an inscrutable collection of formulas. The authors do not provide even the slightest beginning of an insight to a student attempting to learn the material from this text.

Rating:
Summary: nice introduction to survival analysis
Review: The authors present an intermediate level text on survival analysis introducing the concepts and techniques and providing many real examples. Covers all the standard methods including the Cox proportional hazard model (with stratification) and some methods not commonly covered including regression diagnostics and multivariate survival methods (including fraility models).

Rating:
Summary: Good for practitioners, but not for statistician
Review: This book describes formulas and list of applications, but it don't give more accurate statistical reasons. I get how to use the formulas, but i think i am more interested in how to get the formulas