Daniel W.W. Biostatistics: A Foundation for Analysis in the Health Sciences

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WAYNE W. DANIEL

Professor Emeritus

Georgia State University

NINTH EDITION

BIOSTATISTICS

A Foundation for Analysis

in the Health Sciences

JOHN WILEY & SONS, INC.

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Wayne W. Daniel

Biostatistics: A Foundation for Analysis in the Health Sciences, Ninth Edition

ISBN 978-0-470-10582-5

Printed in the United States of America

10987654321

To my wife, Mary,

and my children, Jean,

Carolyn, and John

Special thanks are extended to Professor Chad Cross,

of the School of Public Health at the University of Nevada,

Las Vegas, for his many contributions to this edition.

He has introduced numerous new topics and explanatory comments

that have broadened greatly the scope of the book.

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This ninth edition of Biostatistics: A Foundation for Analysis in the Health Sciences

should appeal to the same audience for which the first eight editions were written:

advanced undergraduate students, beginning graduate students, and health professionals

in need of a reference book on statistical methodology.

Like its predecessors, this edition requires few mathematical prerequisites. Only

reasonable proficiency in algebra is required for an understanding of the concepts and

methods underlying the calculations. The emphasis continues to be on an intuitive

understanding of principles rather than an understanding based on mathematical

sophistication.

For most of the statistical techniques covered in this edition, we discuss the capa-

bilities of one or more software packages (MINITAB, SAS, SPSS, and NCSS) that may

be used to perform the calculations needed for their application. Resulting screen dis-

plays are also shown.

NEW TO THIS EDITION

Chapter Overviews. In this edition, we introduce each chapter with a brief chapter

overview that alerts students to the concepts that they will encounter as they read and

study the chapter. The chapter overviews use non-technical language in order to provide

students with a general understanding of the chapter contents without having to be con-

fronted with unfamiliar terminology.

Leaning Outcomes. Before they begin reading each chapter, students are provided with

a list of learning outcomes that inform them of what they will be expected to know after

having read and studied the chapter. Instructors may also use the learning outcomes as

guides when preparing chapter-by-chapter syllabi.

Summaries of Equations. Where appropriate, students will ﬁnd at the ends of chapters

a summary of the equations that were used in the chapter. This feature will provide stu-

dents with a quick reference source when working on homework assignments. Instruc-

tors who wish to do so may allow students to bring copies of the equation summaries

to the classroom for use during tests.

New Topics. Following is a chapter-by-chapter summary of the topics that are new to

this edition of Biostatistics.

PREFACE

vi PREFACE

Chapter 1 Introduction to Biostatistics. The sampling topic is expanded to include a

discussion of systematic sampling, including comments on stratiﬁed systematic sampling

and stratiﬁed sampling proportional to size. A new section is devoted to the scientiﬁc

method and the design of experiments.

Chapter 2 Descriptive Statistics. Skewness and kurtosis are discussed in considerable

detail and illustrated with computer-generated graphs.

Chapter 3 Some Basic Probability Concepts. The discussion of Bayesian proba-

bility is expanded to enhance students’ understanding of the application of Bayes’s

theorem.

Chapter 4 Probability Distributions. The discussion of probability distributions is

expanded.

Chapter 5 Some Important Sampling Distributions. This chapter is essentially

unchanged.

Chapter 6 Estimation. Several brief comments and new computer output are added for

the purpose of clarifying certain topics.

Chapter 7 Hypothesis Testing. This chapter contains several new computer printouts.

Chapter 8 Analysis of Variance. Additional comments and new computer printouts are

added to help clarify several topics covered in this chapter.

Chapter 9 Simple Linear Regression and Correlation. Several explanatory comments,

a section on testing the regression assumptions, and several computer printouts are new

to this chapter.

Chapter 10 Multiple Regression and Correlation. New to this chapter are several com-

puter printouts and comments for added clariﬁcation.

Chapter 11 Regression Analysis: Some Additional Techniques. The discussion of

regression assumptions is expanded to include the following topics: non-normal data,

unequal error variances, and correlated independent variables. The discussion of variable

selection procedures is expanded to include forward selection and backward elimination

strategies. Discussions of multiple logistic regression and polytomous logistic regression

have been added to the logistic regression section.

Chapter 12 The Chi-Square Distribution and the Analysis of Frequencies. This

chapter contains several new explanatory paragraphs, new examples, and new computer

printouts. The section on survival analysis has been expanded and augmented with new

computer output.

PREFACE vii

Chapter 13 Nonparametric and Distribution-Free Statistics. New explanatory com-

ments and computer printouts have been added in this chapter.

Chapter 14 Vital Statistics. The introduction now includes a paragraph on epidemiology.

SUPPLEMENTS

Instructor’s Solutions Manual. Prepared by Chad Cross, University of Nevada, Las

Vegas. Includes solutions to all problems found in the text. Available only to instructors

who have adopted the text.

New! Student Solutions Manual. Prepared by Chad Cross, University of Nevada, Las

Vegas. Includes solutions to all odd numbered exercises. May be packaged with the text

at a discounted price.

Data Sets. More than 250 data sets of varying sizes have been integrated throughout the

exposition, evidencing this edition’s focus on currency and relevance to modern students.

All examples, section exercises, and review exercises of more then 20 entries are avail-

able at the Wiley Web site below. The large data sets are designed for analysis by the

following techniques: probability (Chapter 3), interval estimation (Chapter 6), hypothesis

testing (Chapter 7), analysis of variance (Chapter 8), simple linear regression (Chapter 9),

multiple regression (Chapter 10), advanced regression analysis (Chapter 11), and chi-

square (Chapter 12). Exercises at the end of these chapters instruct students on how to

use the large data sets. The data sets are available to both instructor and student for down-

load from the Wiley Web site at

www.wiley.com/college/daniel

If you do not have Internet access, please contact the publisher at 111 River Street,

Hoboken, NJ 07030-5774, telephone: 1-877-762-2974 to obtain the electronic ﬁles.

ACKNOWLEDGMENTS

For their many helpful suggestions on how to make this edition of Biostatistics better, I wish

to express my gratitude to the many readers of the previous editions and to the instructors

who have used the book in their classrooms. In particular, I thank the following people who

made valuable recommendations for this revision:

Emilia Bagiella Columbia University

Yi Cheng Indiana University, South Bend

Casey Cremins University of Maryland

Kate Crespi University of California, Los Angeles

Edward Danial Morgan State University

David Elashoff University of California, Los Angeles

Stephen Ganocy Case Western Reserve University

Bhisham Gupta University of Southern Maine

James Halavin Rochester Institute of Technology

Jean Lambert University of Montreal

Mia Markey University of Texas, Austin

Nutan Mishra University of Southern Alabama

Amal Mitra University of Southern Mississippi

Thomas Jay Morrison Ohio Northern University

Theophile Niyonsenga Florida International University

Leonard Onyiah St. Cloud State University

Robert Serﬂing University of Texas, Dallas

Richard Shiavi Vanderbilt University

Pramil Singh Loma Linda University

James Stanley Baylor University

Gary Stanek Youngstown State University

Paul Weiss Emory University

I wish to acknowledge the cooperation of Minitab, Inc. for making available to me over

the years the latest versions of the MINITAB software package for illustrating the use

of the microcomputer in statistical analysis.

I gratefully acknowledge a major contribution to this edition of Biostatistics by

Professor John P. Holcomb of the Department of Mathematics at Cleveland State University,

Cleveland, Ohio.

Thanks go to Professor Chad L. Cross of the School of Public Health at the Univer-

sity of Nevada, Las Vegas, for the new material that he provided for this ninth edition.

Thanks are due to my colleagues at Georgia State University—Professors Geoffrey

Churchill and Brian Schott, who wrote computer programs for generating some of the

Appendix tables—and Professor Lillian Lin, who read the section on logistic regression

and made valuable suggestions for its improvement.

I gratefully acknowledge the help of Dr. James T. Wassell for his help with the

section on survival analysis.

I am grateful to the many researchers in the health sciences ﬁeld who so gener-

ously made available raw data from their research projects. These data appear in the

examples and exercises and are acknowledged individually wherever they appear. I would

also like to thank the editors and publishers of the various journals who gave permission

to reprint data from their publications for use in many of the examples and exercises.

Wayne W. Daniel

viii

PREFACE