Modern Applied Biostatistical Methods: Using S-Plus

Author:   Steve Selvin (Professor of Biostatistics/Epidemiology, Professor of Biostatistics/Epidemiology, University of California School of Public Health, Berkeley, USA)
Publisher:   Oxford University Press Inc
Volume:   28
ISBN:  

9780195120257


Pages:   480
Publication Date:   21 May 1998
Format:   Hardback
Availability:   To order   Availability explained
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Modern Applied Biostatistical Methods: Using S-Plus


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Overview

Statistical analysis typically involves applying theoretically generated techniques to the description and interpretation of collected data. In this text, theory, application and interpretation are combined to present the entire biostatistical process for a series of elementary and intermediate analytic methods. The theoretical basis for each method is discussed with a minimum of mathematics and is applied to a research data example using a computer system called S-PLUS. This system produces concrete numerical results and increases one's understanding of the fundamental concepts and methodology of statistical analysis. Combining statistical logic, data and computer tools, the author explores such topics as random number generation, general linear models, estimation, analysis of tabular data, analysis of variance and survival analysis. The end result is a clear and complete explanation of the way statistical methods can help one gain an understanding of collected data. Modern Applied Biostatistical Methods is unlike other statistical texts, which usually deal either with theory or with applications. It integrates the two elements into a single presentation of theoretical background, data, interpretation, graphics, and implementation. This all-around approach will be particularly helpful to students in various biostatistics and advanced epidemiology courses, and will interest all researchers involved in biomedical data analysis. This text is not a computer manual, even though it makes extensive use of computer language to describe and illustrate applied statistical techniques. This makes the details of the statistical process readily accessible, providing insight into how and why a statistical method identifies the properties of sampled data. The first chapter gives a simple overview of the S-PLUS language. The subsequent chapters use this valuable statistical tool to present a variety of analytic approaches.

Full Product Details

Author:   Steve Selvin (Professor of Biostatistics/Epidemiology, Professor of Biostatistics/Epidemiology, University of California School of Public Health, Berkeley, USA)
Publisher:   Oxford University Press Inc
Imprint:   Oxford University Press Inc
Volume:   28
Dimensions:   Width: 16.00cm , Height: 4.10cm , Length: 23.40cm
Weight:   0.816kg
ISBN:  

9780195120257


ISBN 10:   0195120256
Pages:   480
Publication Date:   21 May 1998
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   To order   Availability explained
Stock availability from the supplier is unknown. We will order it for you and ship this item to you once it is received by us.

Table of Contents

1: S-Language 2: Descriptive Techniques 3: Simulation 4: General Linear Models 5: Estimation: Maximum Likelihood, Bootstrap, Least Squares 6: Analysis of Tabular Data 7: Analysis of Variance and Some Other S-Functions 8: Rates, Life Tables and Survival

Reviews

Noted in Technometrics This book...,is unique in providing the instructor with a computational approach to these topics as well as their conceptual presentation....I would recommend this book to any instructor teaching biostatistics courses, and especially to students interested in application. --Doody's Journal This book flows nicely and is enjoyable to read...A wealth of examples are helpful for targeted biostatistical analyses and/or building one's understanding of S-PLUS. --JASA, June 2001


Author Information

Steve Selvin, Ph.D., is Professor of Biostatistics and Epidemiology at the University of California School of Public Health, Berkeley. He is also the author of Statistical Analysis of Epidemiologic Data, 2nd ed. (OUP, 1996).

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