BIOSTATISTICS A Foundation For Analysis For The Health Sciences

956 Pages·2012·13.25 MB·English

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NINTH EDITION
BIOSTATISTICS
A Foundation for Analysis
in the Health Sciences
WAYNE W. DANIEL
Professor Emeritus
Georgia State University
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
10 9 8 7 6 5 4 3 2 1
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.
This page intentionally left blank
PREFACE
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.
v
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: [phone] to obtain the electronic files.
ACKNOWLEDGMENTS
For their many helpful suggestions on how to make this edition of Biostatisticsbetter, 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
viii PREFACE
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