For readers with a minimal background in statistics, this text shows how to analyze and interpret epidemiological and medical survival data.
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This practical guide to the analysis of survival data written for readers with a minimal background in statistics explains why the analytic methods work and describes how to effectively analyze and interpret epidemiologic and medical survival data with the help of modern computer systems.The text contains a variety of statistical methods that not only are key elements of survival analysis but also are central to statistical analysis in general. Techniques such as statistical tests, transformations, confidence intervals, and analytic modeling are discussed in the context of survival data but are, in fact, statistical tools that apply to many kinds of data. Similarly, discussions of such statistical concepts as bias, confounding, independence, and interaction are presented and also are basic to a broad range of applications. These topics make up essentially a second-year, one-semester biostatistics course in survival analysis concepts and techniques for nonstatisticians.
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