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Analytic procedures suitable for the study of human disease are scattered throughout the statistical and epidemiologic literature. Explanations of their properties are frequently presented in mathematical and theoretical language. This well-established text gives readers a clear understanding of the statistical methods that are widely used in epidemiologic research without depending on advanced mathematical or statistical theory. By applying these methods to actual data, Selvin reveals the strengths and weaknesses of each analytic approach. He combines techniques from the fields of statistics, biostatistics, demography and epidemiology to present a comprehensive overview that does not require computational details of the statistical techniques described.For the Third Edition, Selvin took out some old material (e.g. the section on rarely used cross-over designs) and added new material (e.g. sections on frequently used contingency table analysis). Throughout the text he enriched existing discussions with new elements, including the analysis of multi-level categorical data and simple, intuitive arguments that exponential survival times cause the hazard function to be constant. He added a dozen new applied examples to illustrate such topics as the pitfalls of proportional mortality data, the analysis of matched pair categorical data, and the age-adjustment of mortality rates based on statistical models. The most important new feature is a chapter on Poisson regression analysis. This essential statistical tool permits the multivariable analysis of rates, probabilities and counts.
This text investigates the application of statistical methods to epidemiologic data, aiming to bridge the gap between complex theoretical literature and practical research needs. Prof. Steve Selvin, a recognized expert in biostatistics, provides a framework that prioritizes conceptual understanding over advanced mathematical derivation. By utilizing real-world data sets, the author demonstrates the utility and limitations of various analytic approaches, ensuring that researchers can select appropriate tools for human disease studies without needing deep computational expertise.
What You Will Find
Experts and researchers frequently cite this work as a foundational resource for those seeking to apply statistical rigor to public health data without becoming bogged down in excessive theoretical abstraction. The text is widely regarded for its clarity and its ability to make complex biostatistical concepts accessible to practitioners in the field.
Page Count:
512
Publication Date:
2004-05-13
Publisher:
Oxford University Press
ISBN-10:
0195172809
ISBN-13:
9780195172805
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