(s/dev) Statistical Analysis Of Epidemiologic Data (3 Ed): 35 (Monographs in Epidemiology and Biostatistics) - Tapa dura

"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 From reviews of previous editions: "This book is well-written and is generally easy to read. Selvin has done a nice job of presenting methods and illustrating the methods with numerical data."--Journal of the American Statistical Association ..".an outstanding, readable, and useful presentation of the methods of analysis of disease data. The author has filled a gap admirably. I am sure that this book will deservedly become extensively used in the field of epidemiology world-wide..."--International Journal of Health Sciences "This is a well-written book that provides an important link between the analysis and interpretation of continuous data in epidemiologic terms. The text would be useful in an immediate epidemiology course that describes the basics of life-table analysis, logistic regression, and survival analysis."--Epidemiology Monitor

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.