Statistical Methods for the Analysis of Biomedical Data

The new edition adds a chapter on multiple linear regression in biomedical research, with sections including the multiple linear regressions model and least squares; the ANOVA table, parameter estimates, and confidence intervals; partial f-tests; polynomial regression; and analysis of covariance.
* Organized by problem rather than method, so it guides readers to the correct technique for solving the problem at hand.Dieser Band behandelt eine Reihe statistischer Themen, die bei der Analyse biologischer und medizinischer Daten allgemein Anwendung finden. Diese 2. Auflage wurde komplett überarbeitet, aktualisiert und erweitert. Einige Kapitel sind neu hinzugekommen, u.a. zur multiplen linearen Regression in der biomedizinischen Forschung. Der Stoff ist so gegliedert, dass der Leser den Text unabhängig von der jeweiligen statistischen Methode leicht nach Problemstellungen durchsuchen kann. Mit zahlreichen durchgearbeiteten Beispielen, die detaillierte Lösungsangaben zu Problemen aus der Praxis liefern.

Dedication v

Preface to the 1987 Edition xvii

Preface to the 2002 Edition xxi

Acknowledgment xxiii

1 Introduction 1

2 Descriptive Statistics 9

3 Basic Probability Concepts 49

4 Further Aspects of Probability 79

5 Confidence Intervals and Hypothesis Testing: General Considerations and Applications 119

6 Comparison of Two Groups: t-Tests and Rank Tests Introduction 151

7 Comparison of Two Groups: Chi-Square and Related Procedures 217

8 Tests of Independence and Measures of Association for Two Random Variables 263

9 Least-Squares Regression Methods: Predicting One Variable from Another 307

10 Comparing More than Two Groups Observations: Analysis of Variance for Comparing Groups 359

11 Comparing More than Two Groups of Observations: Rank Analysis of Variance for Group Comparisons 417

12 Comparing More than Two Groups of Observations: Chi-Square and Related Procedures 441

13 Special Topics in Analysis of Epidemiologic and Clinical Data: Studying Association between a Disease and a Characteristic 461

14 Estimation and Comparison of Survival Curves 509

15 Multiple Linear Regression Methods: Predicting One Variable from Two or More Other Variables 541

Appendix 623

Topic Index 673

"…useful in a course in biostatistics." (Journal of Statistical Computation and Simulation, September 2005)

"...a nice overview of statistical topics...an excellent book to have...highly recommend this book for students and researchers..." (Statistical Methods in Medical Research, Vol 13, 2004)

"…interesting and useful…I recommend it as an addition to your statistical library, and if you already own the first edition, it would be worthwhile to update it." (The American Statistician, Vol. 58, No. 2, May 2004)

ROBERT F. WOOLSON, PhD, is a Professor of Biostatistics and Associate Dean for Research at the University of Iowa College of Public Health.
WILLIAM R. CLARKE, PhD, is a Professor of Biostatistics at the University of Iowa College of Public Health. Praise for the First Edition

"This text is a very welcome addition to the field, both as a reference and classroom text."
-Publication of the International Statistical Institute

"This book is a perfectly organized source of reference for elementary statistical procedures used in clinical trials."
-Biomedical Journal

"I would recommend this book as an introductory biostatistics text for its clear presentation and worked examples, particularly in the chapters on the comparison of groups."
-Statistics in Medicine

Statistical Methods for the Analysis of Biomedical Data surveys a number of statistical topics commonly used in the analysis of biological and medical data, as well as several other topics such as observer agreement, standardization of rates, and methods for analysis of odds ratio. Applied in its approach, the book describes statistical procedures through the introduction of worked examples for each procedure.

The Second Edition includes a new chapter on multiple linear regression methods, new sections in each chapter on using SAS for computations, and revised and expanded problems. This authoritative volume also:
* Is organized by problem rather than method, guiding readers to the correct technique for solving the problem at hand
* Compares, in cases where more than one technique is applicable, the advantages and disadvantages of each option
* Develops, in detail, solutions to practical problems of design and analysis through worked examples
* Demonstrates how SAS output illustrates the results of analyses of true-to-life applications, such as predicting systolic blood pressure as a function of age, height, weight, and gender from data taken on Muscatine teenagers
* Includes methods for comparing two or more groups and evaluating the association between two variables, techniques for epidemiological analysis of 2x2 tables, and procedures for estimation and comparing survival curves

Statistical Methods for the Analysis of Biomedical Data makes an ideal reference for analysts and researchers in biostatistics, medicine, and other health-related fields, as well as a textbook for graduate courses in biostatistics.