Survival Analysis : A Self-Learning Text (Statistics for Biology and Health)
Editorial Reviews
Book Description
This text on survival analysis provides a straightforward and easy-to-follow introduction to the main concepts and techniques of the subject. It is based on numerous courses given by the author to students and researchers in the health sciences and is written with such readers in mind. Throughout, there is an emphasis on presenting each new topic motivated with real examples of a survival analysis investigation, and then presenting thorough analyses of real data sets. Each chapter concludes with practice exercises to help readers reinforce their understanding of the concepts covered in the chapter. Readers can then extend their knowledge with a more thoroughgoing test. Answers to both are included. Beginning with the basic concepts of survival analysis-time to an event as a variable, censored data, and the hazard function-the author then introduces the Kaplan-Meier survival curves, the log-rank test, the Peto test, and the most widely used technique in survival analysis, the Cox proportional hazards model. Later chapters cover techniques for evaluating the proportional hazards assumptions, the stratified Cox procedure, and extending the Cox model to time-dependent variables. Readers will enjoy David Kleinbaum's style of presentation with numerous figures and diagrams illustrating each idea. As a result, this text makes an excellent introduction for all those coming to the subject for the first time.
Book Info
Emory University, Atlanta, GA. Self-paced textbook for epidemiology students with formulas, extensive practice exercises and answers. Each chapter has extensive pedagogy and detailed explanations. Easy to follow diagrams.
Survival Analysis: A Self-Learning Text (Statistics for Biology and Health),David Kleinbaum,Mitchel Klein,Springer,0387945431,Applied,Biometry,Biostatistics,Medical / Nursing,Probability & Statistics - General,Science/Mathematics,Survival analysis (Biometry),Applied mathematics,Medical / Biostatistics,Medicine,Probability & statistics,Survival Analysis
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