Table of Contents
Cover
Title page
Copyright page
Preface
CHAPTER 1 The What, Why, and How of Biostatistics in Medical Research
1.1 DEFINITION OF STATISTICS AND BIOSTATISTICS
1.2 WHY STUDY STATISTICS?
1.3 THE MEDICAL LITERATURE
1.4 MEDICAL RESEARCH STUDIES
CHAPTER 2 Sampling from Populations
2.1 DEFINITIONS OF POPULATIONS AND SAMPLES
2.2 SIMPLE RANDOM SAMPLING
2.3 SELECTING SIMPLE RANDOM SAMPLES
2.4 OTHER SAMPLING METHODS
2.5 GENERATING BOOTSTRAP SAMPLES
CHAPTER 3 Graphics and Summary Statistics
3.1 CONTINUOUS AND DISCRETE DATA
3.2 CATEGORICAL DATA
3.3 FREQUENCY HISTOGRAMS
3.4 STEM-AND-LEAF DIAGRAMS
3.5 BOX PLOTS
3.6 BAR AND PIE CHARTS
3.7 MEASURES OF THE CENTER OF A DISTRIBUTION
3.8 MEASURES OF DISPERSION
CHAPTER 4 Normal Distribution and Related Properties
4.1 AVERAGES AND THE CENTRAL LIMIT THEOREM
4.2 STANDARD ERROR OF THE MEAN
4.3 STUDENT’S T-DISTRIBUTION
CHAPTER 5 Estimating Means and Proportions
5.1 THE BINOMIAL AND POISSON DISTRIBUTIONS
5.2 POINT ESTIMATES
5.3 CONFIDENCE INTERVALS
5.4 SAMPLE SIZE DETERMINATION
5.5 BOOTSTRAP PRINCIPLE AND BOOTSTRAP CONFIDENCE INTERVALS
CHAPTER 6 Hypothesis Testing
6.1 TYPE I AND TYPE II ERRORS
6.2 ONE-TAILED AND TWO-TAILED TESTS
6.3 P-VALUES
6.4 COMPARING MEANS FROM TWO INDEPENDENT SAMPLES: TWO-SAMPLE T-TEST
6.5 PAIRED T-TEST
6.6 TESTING A SINGLE BINOMIAL PROPORTION
6.7 RELATIONSHIP BETWEEN CONFIDENCE INTERVALS AND HYPOTHESIS TESTS
6.8 SAMPLE SIZE DETERMINATION
6.9 BOOTSTRAP TESTS
6.10 MEDICAL DIAGNOSIS: SENSITIVITY AND SPECIFICITY
6.11 SPECIAL TESTS IN CLINICAL RESEARCH
6.12 REPEATED MEASURES ANALYSIS OF VARIANCE AND LONGITUDINAL DATA ANALYSIS
6.13 META-ANALYSIS
CHAPTER 7 Correlation, Regression, and Logistic Regression
7.1 RELATIONSHIP BETWEEN TWO VARIABLES AND THE SCATTER PLOT
7.2 PEARSON’S CORRELATION
7.3 SIMPLE LINEAR REGRESSION AND LEAST SQUARES ESTIMATION
7.4 SENSITIVITY TO OUTLIERS AND ROBUST REGRESSION
7.5 MULTIPLE REGRESSION
7.6 LOGISTIC REGRESSION
CHAPTER 8 Contingency Tables
8.1 2 × 2 TABLES AND CHI-SQUARE
8.2 SIMPSON’S PARADOX IN THE 2 × 2 TABLE
8.3 THE GENERAL R × C TABLE
8.4 FISHER’S EXACT TEST
8.5 CORRELATED PROPORTIONS AND MCNEMAR’S TEST
8.6 RELATIVE RISK AND ODDS RATIO
CHAPTER 9 Nonparametric Methods
9.1 RANKING DATA
9.2 WILCOXON RANK-SUM TEST
9.3 SIGN TEST
9.4 SPEARMAN’S RANK-ORDER CORRELATION COEFFICIENT
9.5 INSENSITIVITY OF RANK TESTS TO OUTLIERS
CHAPTER 10 Survival Analysis
10.1 TIME-TO-EVENT DATA AND RIGHT CENSORING
10.2 LIFE TABLES
10.3 KAPLAN–MEIER CURVES
10.4 PARAMETRIC SURVIVAL CURVES
10.5 COX PROPORTIONAL HAZARD MODELS
10.6 CURE RATE MODELS
Solutions to Selected Exercises
APPENDIX: Statistical Tables
References
Author Index
Subject Index
Copyright © 2011 by John Wiley & Sons, Inc. All rights reserved.
Published by John Wiley & Sons, Inc., Hoboken, New Jersey.
Published simultaneously in Canada.
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Library of Congress Cataloging-in-Publication Data:
Chernick, Michael R.
The essentials of biostatistics for physicians, nurses, and clinicians / Michael R. Chernick.
p. ; cm.
Includes bibliographical references and index.
ISBN 978-0-470-64185-9 (pbk.)
1. Biometry. I. Title.
[DNLM: 1. Biostatistics. WA 950]
QH323.5C484 2011
570.1'5195–dc22
2011002198
oBook ISBN: 978-1-118-07195-3
ePDF ISBN: 978-1-118-07193-9
ePub ISBN: 978-1-118-07194-6
I have taught biostatistics in the health sciences and published a book in 2003 with Wiley on that topic. That book is a textbook for upper-level undergraduates and graduate students in the health science departments at universities. Since coming to the Lankenau Institute 17 months ago, I was tasked to prepare a course in biostatistics for nurses and physicians (particularly the hospital residents and fellows that do medical research). I quickly learned that although the material in my book was relevant, it contained too much material and was not in a digestible form for them. I prepared a six-lecture course (1 hour each) for physicians, and a two-lecture course for the nurses. To prevent boredom, I introduced some funny but educational cartoon slides. The course currently exists and has been refined as PowerPoint presentations and has been moderately successful. I also am starting a similar course at statistics.com.
The physicians and nurses have a busy schedule, and what they need is a concise and clearly explained set of lectures that cover only the areas of statistics that are essential to know about in medical research. This means topics that are not taught in traditional introductory statistics courses. So Kaplan–Meier curves, repeated measures analysis of variance, hazard ratios, contingency tables, logrank tests, bioequivalence, cross-over designs, noninferiority, selection bias, and group sequential methods are all included, but they are introduced on a conceptual level without the need for theory. It is when and why these methods work that they need to know, and not a detailed account of how they work mathematically. I feel that it would be appropriate to have a textbook for such a course that can be taught in-house at research centers or online courses. The book is intended to be approximately 160 pages along with suitable references.
I am very grateful to Professor Marlene Egger, who carefully reviewed the manuscript and made several wonderful suggestions that helped with the clarity and improved the content of the book.
Michael R. Chernick