Statistical Methods for the Analysis of Biomedical Data

by William R. Clarke and Robert F. Woolson

A variety of statistical methods are described and compared by this book, for the analysis of biomedical data. Statistical procedures are described by presenting worked examples for each type of procedure. Coverage includes: methods for comparing two groups, methods for evaluating the association between two variables, techniques for epidemiological analysis of 2 x 2 tables and procedures for estimation and comparison of survival curves. Both parametric and non-parametric procedures are presented throughout the text, and additional topics detailed include observer agreement, standardization of rates and methods for analysis of odds ratio.

• Format: Hardcover
• Language: English
• ISBN: 0471806153
• ISBN13: 9780471806158
• Release Date: September 1987
• Publisher: Wiley
• Length: 544 Pages
• Weight: 1.95 lbs.
• Dimensions: 1.2" x 6.3" x 9.3"

Customer Reviews

great comprehensive and rigorous treatment of biostatistics

This is the second edition of a highly acclaimed text. Like the first edition this book gives an excellent overview of statistical problems in the medical field and provides illustrations of a variety of parametric and nonparametric statistical techniques for solving these problems. It is aimed at the intermediate level rather than as an introductory course. So medical professionals, with a first course in biostatistics under their belt, will find this useful. It is also a good text for graduate students in statistics or biostatistics. Examples are illustrated throughout the text using SAS software. This is a key addition to this edition of the book. Also added in this edition is a chapter on multiple regression where various model selection procedures are nicely covered. A nice feature of the book is its coverage of epidemiologic methods and data. This was also a strength of the first edition. I was a little disappointed that the authors did not take the opportunity to significantly update the bibliography. Only a few references are given in the latter chapters to books and articles that appeared after the publication of the first edition in 1987. Also, the authors missed an opportunity to discuss the advances in computing that have led to new methods including Markov Chain Monte Carlo and resampling, both of which have found many applciations in medical research. Bioinformatics and advances in genetics are also playing a major role in medical research, having blossomed since the publication of the first edition of the book. Although I would not expect these topics to necessarily get much coverage, I think they are important enough to at least be mentioned and discussed and have key articles and books referenced. This is an excellent text for a second course in biostatistics for health care professionals. For a first course the book I am writing with Bob Friis will be useful and it is up to date and even provides some coverage of resampling methods. Wiley published the second edition in 2003.

nice reference for biostatisticians & medical professionals

This is the second edition of a highly acclaimed text. Like the first edition this book gives an excellent overview of statistical problems in the medical field and provides illustrations of a variety of parametric and nonparametric statistical techniques for solving these problems. It is aimed at the intermediate level rather than as an introductory course. So medical professionals, with a first course in biostatistics under their belt, will find this useful. It is also a good text for graduate students in statistics or biostatistics. Examples are illustrated throughout the text using SAS software. This is a key addition to this edition of the book. Also added in this edition is a chapter on multiple regression where various model selection procedures are nicely covered.A nice feature of the book is its coverage of epidemiologic methods and data. This was also a strength of the first edition.I was a little disappointed that the authors did not take the opportunity to significantly update the bibliography. Only a few references are given in the latter chapters to books and articles that appeared after the publication of the first edition in 1987. Also, the authors missed an opportunity to discuss the advances in computing that have led to new methods including Markov Chain Monte Carlo and resampling, both of which have found many applciations in medical research. Bioinformatics and advances in genetics are also playing a major role in medical research, having blossomed since the publication of the first edition of the book. Although I would not expect these topics to necessarily get much coverage, I think they are important enough to at least be mentioned and discussed and have key articles and books referenced.This is an excellent text for a second course in biostatistics for health care professionals. For a first course the book I am writing with Bob Friis will be useful and it is up to date and even provides some coverage of resampling methods. It will be published by Wiley in early 2003.