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(More customer reviews)Kleinbaum's Survival Analysis: A Self-Learning Text is an excellent nontechnical introduction to survival analysis. Survival analysis are statistical techniques that addresses the problem of how much time it takes for an event to occur. The techniques is widely used in medical research, and my interest in it comes from wanting to explore how long it will take for a person to refinance a loan. Kleinbaum explores the topic in a straightforward, and easy-to-follow manner. The topics are illustrated through numerous figures, diagrams, and analysis of real data sets. Kleinbaum uses a minimial amount of mathematics and carefully leads the reader through any math that is used. The book concentrates on the Cox Proportional Hazard model which is the most widely used technique in survival analysis. Given the introductory nature of the book one will not find materials covering other models. Someone with some mathematical knowledge, one semester of calculus, and a semester of statistics and a semester of undergraduate econometrics would get the most out of this book. If you are looking for an introduction to survival analysis this is a great place to start. I feel I have a strong foundation to start using survival analysis at my job and continue with a more technical exploration.
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An excellent introduction for all those coming to the subject for the first time.New material has been added to the second edition and the original six chapters have been modified.The previous edition sold 9500 copies world wide since its release in 1996.Based on numerous courses given by the author to students and researchers in the health sciences and is written with such readers in mind. Provides a "user-friendly" layout and includes numerous illustrations and exercises. Written in such a way so as to enable readers learn directly without the assistance of a classroom instructor. Throughout, there is an emphasis on presenting each new topic backed by real examples of a survival analysis investigation, followed up with thorough analyses of real data sets.
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