This text combines applied and theoretical approaches to the analysis of epidemiologic issues. It goes beyond elementary material to deal with real problems generated by disease data, and delves into less usual areas such as the analysis of spatial distributions, survival data, proportional hazards regression, and "computer intensive" approaches to statistical estimation. Each method discussed in the text is illustrated with examples which include complete sets of data. Using actual data demonstrates the strengths and weaknesses of different analytic approaches in describing a disease process. The book's goal is to develop a clear understanding of analytic approaches to problems in epidemiological data analysis without relying on sophisticated mathematics and advanced statistical theory. Individuals with some background in epidemiology and statistics will find this a useful volume in the study of epidemiological analysis.
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Steve Selvin is at University of California, Berkeley.
"This book covers a large number of statistical methods useful in analyzing epidemiologic data. The material is clearly presented and is illustrated by interesting examples based on real data. Most of the examples are analyzed by more than one method and, when models are used, by more than one model. This is extremely helpful in understanding the relationship between different analytic techniques. This should be a valuable reference book for statisticians and epidemiologists, and a good text for an intermediate level course." --Suzanne Hudson, Department of Biostatistics, East Carolina University
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