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Biostatistical Methods in Epidemiology

Autor Stephen C Newman
en Limba Engleză Hardback – 10 aug 2001
An introduction to classical biostatistical methods in epidemiology Biostatistical Methods in Epidemiology provides an introduction to a wide range of methods used to analyze epidemiologic data, with a focus on nonregression techniques. The text includes an extensive discussion of measurement issues in epidemiology, especially confounding. Maximum likelihood, Mantel-Haenszel, and weighted least squares methods are presented for the analysis of closed cohort and case-control data. Kaplan-Meier and Poisson methods are described for the analysis of censored survival data. A justification for using odds ratio methods in case-control studies is provided. Standardization of rates is discussed and the construction of ordinary, multiple decrement and cause-deleted life tables is outlined. Sample size formulas are given for a range of epidemiologic study designs. The text ends with a brief overview of logistic and Cox regression. Other highlights include:
  • Many worked examples based on actual data
  • Discussion of exact methods
  • Recommendations for preferred methods
  • Extensive appendices and references
Biostatistical Methods in Epidemiology provides an excellent introduction to the subject for students, while also serving as a comprehensive reference for epidemiologists and other health professionals.
For more information, visit www.wiley.com/mathematics
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Specificații

ISBN-13: 9780471369141
ISBN-10: 0471369144
Pagini: 408
Dimensiuni: 161 x 240 x 26 mm
Greutate: 0.78 kg
Ediția:00004
Editura: Wiley
Locul publicării:Hoboken, United States

Public țintă

Text in graduate courses in biostatsitics and epidemiology.

Descriere

An introduction to classical biostatistical methods in epidemiology, this text provides an introduction to a range of methods used to analyze epidemiologic data, with a focus on nonregression techniques. It also includes a discussion of measurement issues in epidemiology, especially confounding, with an overview of logistic and Cox regression.