Statistical Methods in Epidemiologic Research

Transcription

1 Statistical Methods in Epidemiologic Research Ray M. Merrill, PhD, MPH, MS, FACE, FAAHB Professor Brigham Young University Provo, Utah _FMxx_00i_xviii.indd 1

2 World Headquarters Jones & Bartlett Learning 5 Wall Street Burlington, MA info@jblearning.com Jones & Bartlett Learning books and products are available through most bookstores and online booksellers. To contact Jones & Bartlett Learning directly, call , fax , or visit our website, Substantial discounts on bulk quantities of Jones & Bartlett Learning publications are available to corporations, professional associations, and other qualified organizations. For details and specific discount information, contact the special sales department at Jones & Bartlett Learning via the above contact information or send an to specialsales@jblearning.com. Copyright 2016 by Jones & Bartlett Learning, LLC, an Ascend Learning Company All rights reserved. No part of the material protected by this copyright may be reproduced or utilized in any form, electronic or mechanical, including photocopying, recording, or by any information storage and retrieval system, without written permission from the copyright owner. The content, statements, views, and opinions herein are the sole expression of the respective authors and not that of Jones & Bartlett Learning, LLC. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not constitute or imply its endorsement or recommendation by Jones & Bartlett Learning, LLC and such reference shall not be used for advertising or product endorsement purposes. All trademarks displayed are the trademarks of the parties noted herein. Statistical Methods in Epidemiologic Research is an independent publication and has not been authorized, sponsored, or otherwise approved by the owners of the trademarks or service marks referenced in this product. There may be images in this book that feature models; these models do not necessarily endorse, represent, or participate in the activities represented in the images. Any screenshots in this product are for educational and instructive purposes only. Any individuals and scenarios featured in the case studies throughout this product may be real or fictitious, but are used for instructional purposes only. This publication is designed to provide accurate and authoritative information in regard to the Subject Matter covered. It is sold with the understanding that the publisher is not engaged in rendering legal, accounting, or other professional service. If legal advice or other expert assistance is required, the service of a competent professional person should be sought. Production Credits VP, Executive Publisher: David D. Cella Publisher: Michael Brown Associate Editor: Lindsey Mawhiney Associate Editor: Nicholas Alakel Production Manager: Tracey McCrea Senior Marketing Manager: Sophie Fleck Teague Manufacturing and Inventory Control Supervisor: Amy Bacus To order this product, use ISBN: Library of Congress Cataloging-in-Publication Data Merrill, Ray M., author. Statistical methods in epidemiologic research / Ray M. Merrill. p. ; cm. Includes bibliographical references and index. ISBN (paperback) I. Title. [DNLM: 1. Epidemiologic Methods. WA 950] R853.S dc Printed in the United States of America Composition: Cenveo Publisher Services Cover Design: Michael O Donnell Rights & Media Research Coordinator: Mary Flatley Media Development Editor: Shannon Sheehan Cover Image: Hluboki Dzianis/Shutterstock Printing and Binding: Edwards Brothers Malloy Cover Printing: Edwards Brothers Malloy _FMxx_00i_xviii.indd 2

3 Dedication To Marty, Pat, and Phil iii _FMxx_00i_xviii.indd 3

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5 Contents Dedication...iii About the Author... xv Preface...xvii Section I: Basic Concepts in Epidemiology and Statistics 1 Chapter 1: The Basics of Epidemiology 3 Defining Epidemiology...3 Path to Modern Epidemiology...8 Epidemiologic Research...13 Summary...16 Exercises...18 References...21 Chapter 2: Principles of Statistics 29 Statistics in Epidemiology...29 Basic Statistical Concepts...30 Data...30 Describing Data...31 Probability...31 Sampling...43 Estimation in Statistics...44 Hypothesis Testing...46 Decision Errors...47 Applications of Hypothesis Testing...48 Statistical Techniques...53 Summary...54 Exercises...56 References...60 Chapter 3: Causality in Epidemiology 63 Basic Concepts...63 Models of Causation...66 Causal Diagrams...70 v _FMxx_00i_xviii.indd 5

6 vi Contents Flow Diagrams...71 Full Chain Approach...72 Philosophy of Scientific Inference...73 Induction...73 Refutation...74 Consensus...74 Bayesian...75 Guides for Thinking about Causality...75 Interaction Among Causes...79 Summary...80 Exercises...81 References...83 Chapter 4: Epidemiologic Data 87 Outcome Data...88 Exposure Data...91 Direct Measures of Exposure...93 Indirect Measures of Exposure...94 Precision...97 Precision Assessment...98 Internal Consistency...98 Cronbach s Alpha...98 Intra-rater or Intra-measurement Reliability Inter-rater Reliability or Concordance Accuracy Validity Validity Assessment Receiver Operating Characteristic Curves Summary Exercises References Chapter 5: Sample Size, Power, and Probability Sampling 129 Criteria for Estimating Sample Size Sample Size Techniques for Descriptive Studies _FMxx_00i_xviii.indd 6

7 Contents vii Sample Size Techniques for Analytic Studies Other Sample Size Issues Dropouts Fixed Sample Size Minimize Sample Size and Maximize Power SAS for Computing Power and Sample Size Probability Sampling Summary Exercises References Summary of Sample Size Techniques for Descriptive Studies Summary of Sample Size Techniques for Analytic Studies Summary of Other Sample Size Issues Chapter 6: Measures of Frequency and Association 167 Ratios, Proportions, and Rates Frequency Measures Incidence Rate (Person-Time Rate) Cumulative Incidence Prevalence Proportions Other Rates Standardizing Rates Measures of Association Relative Risk Odds Ratio Prevalence Ratio Attributable Risk Preventive Fraction (Preventable Fraction) Summary Exercises References Chapter 7: Disease Surveillance and Screening 203 History Attributes of Surveillance _FMxx_00i_xviii.indd 7

8 viii Contents Elements of Surveillance System Case Definition Population under Surveillance Confidentiality Cooperation Ease of Reporting Approaches to Surveillance Active versus Passive Surveillance Notifiable Disease Reporting Laboratory-based Surveillance Registries Surveys Information Systems Sentinel Events Record Linkage Summary Analysis, Interpretation, and Presentation of Surveillance Data Analysis Interpretation Presentation Summary Exercises References Section II: Epidemiologic Study Designs 227 Chapter 8: Designing Epidemiologic Research 229 Exploratory Research Literature Reviews Depth Interviews Focus Groups Case Analyses Descriptive Research Analytical Research Exploratory versus Confirmatory Data Analysis Techniques _FMxx_00i_xviii.indd 8

9 Contents ix Improving Accuracy of the Study Design Chance Bias Information Bias Temporal Bias Biases in Screening Volunteer Bias Prevalence-Incidence Bias Lead Time Bias Length Bias Detection Bias Selection Bias Stage Migration Bias Pseudodisease (Overdiagnosis) Confounding Bias Statistical Adjustment Propensity Scores Standardization Randomization Bias According to Study Design Summary Exercises References Chapter 9: Descriptive Studies 273 Descriptive Research Descriptive Measures Characteristics of Person, Place, and Time Person Population Pyramid Place Time Time-Series Descriptive Study Designs Ecologic Studies Case Reports and Case Series Cross-sectional Studies _FMxx_00i_xviii.indd 9

10 x Contents Summary Exercises References Chapter 10: Analytic Studies 333 Case-Control Study Selection of Cases Selection of Controls Matching in Case-Control Studies Exposure Status Case-Crossover Study Cohort Study Types of Cohort Studies Classifying the Exposure Outcome Events, Timing, and Other Issues Cohort Study Advantages and Disadvantages Comparison of Case-Control and Cohort Studies Summary Exercises References Chapter 11: Experimental Studies 371 Experimental Study Designs Random Assignment Blinding Nonrandom Assignment Clinical Phases in Testing New Therapies Pilot Studies Designing a Clinical Trial Selecting the Intervention Selecting the Outcome Assembling the Study Cohort Randomization and Blinding Measuring Baseline Variables Ensuring Compliance Monitoring Plan _FMxx_00i_xviii.indd 10

11 Contents xi Summary Exercises References Section III: Statistical Techniques and Epidemiologic Application 403 Chapter 12: Statistical Models 405 Regression Function Simple Linear Regression Multiple Regression General Linear Model Generalized Linear Model Linear Regression Logistic Regression Poisson Regression Cox Proportional Hazards Model Methods of Estimation and Assessment Ordinary Least Squares Maximum Likelihood Estimation Mixed Models Summary Exercises References Chapter 13: General Linear Models 437 t Statistic F Statistic Analysis of Variance Multivariate Analysis of Variance Repeated Measures Analysis of Variance Other Multivariate Models Time-Series Models Time-Series and Dummy Variables Autoregressive Models Durbin Watson Test _FMxx_00i_xviii.indd 11

12 xii Contents Effect Modification and Confounding Other Applications Estimating Selected Epidemiologic Measures Pooled Estimates Identifying Change in Trends Summary Exercises References Chapter 14: Categorical Data Analysis 503 Proportion in a Single Group Proportions in Paired Groups Proportions in Two Independent Groups Chi-Square and Fisher s Exact Tests Other Applications of the Chi-Square Homogeneity of Odds Ratios Logistic Regression Logistic Regression: Ordinal Response Logistic Regression: Nominal Response Conditional Logistic Regression Poisson Regression Summary Exercises References Section IV: Special Topics 555 Chapter 15: Nonparametric Methods 557 Spearman s Rank Correlation Coefficient Wilcoxon Signed-Rank Test Wilcoxon Rank Sum Test Kruskal Wallis Test Rank Analysis of Covariance Nonparametric Tests for Time Series Data (Optional) Runs Test Turning Points Test _FMxx_00i_xviii.indd 12

13 Contents xiii Sign Test Daniels Test for Trend Trend Test Based on Kendall s Tau Von Neumann s Rank Ratio Test Summary Exercises References Chapter 16: Life Tables 607 Calculation of the Probability of Dying (q x ) Calculation of the Remaining Life Table Abridging the Complete Life Table Multiple-Cause Life Table Years of Potential Life Lost Summary Exercises References Chapter 17: Survival Analysis 639 Terminology and Notation Parametric Regression Techniques Cox Proportional Hazards Regression Life Table Method Kaplan Meier Method Log-Rank Test Summary Exercises References Appendix A: Statistical Notation 685 Notation Probability Hypothesis Testing Random Variables Special Symbols Selected Formulas and Equations _FMxx_00i_xviii.indd 13

14 xiv Contents Appendix B: Answers to Chapter Questions 697 Chapter Chapter Chapter Chapter Chapter Chapter Chapter Chapter Chapter Chapter Chapter Chapter Chapter Chapter Chapter Chapter Chapter Appendix C: Computing with SAS 793 SAS Data Step Importing Data Exporting Data Manipulating Data in SAS SAS Procedures Appendix D: Tables 805 Glossary Key Terms Index _FMxx_00i_xviii.indd 14

15 about the AUTHOR Ray M. Merrill, PhD, MPH received his academic training in statistics and public health. In 1995, he was named a Cancer Prevention Fellow at the National Cancer Institute, where he worked in the Surveillance Modeling and Methods Section of the Applied Research Branch. In 1998, he joined the faculty of the Department of Health Science at Brigham Young University in Provo, Utah, where he has been active in teaching and research. In 2001, he spent a sabbatical working in the Unit of Epidemiology for Cancer Prevention at the International Agency for Research on Cancer Administration in Lyon, France. He has won various awards for his research and is a Fellow of the American College of Epidemiology and of the American Academy of Health Behavior. He is the author of over 250 peer-reviewed publications, including Environmental Epidemiology, Reproductive Epidemiology, Principles of Epidemiology Workbook, Fundamentals of Epidemiology and Biostatistics, Introduction to Epidemiology, and the forthcoming Behavioral Epidemiology with Jones & Bartlett Learning. Dr. Merrill teaches classes in epidemiology and biostatistics and is a full professor in the Department of Health Science, College of Life Sciences, at Brigham Young University. xv _FMxx_00i_xviii.indd 15

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17 preface The field of epidemiology has come a long way since the days of infectious disease investigations performed by Thomas Sydenham, Louis Pasteur, Robert Koch, and John Snow. Back then, epidemiologists had the primary challenge of isolating a single bacteria, virus, or parasite in order to control infectious disease outbreaks. In modern times, advances in nutrition, housing conditions, sanitation, water supply, antibiotics, and immunization programs have helped control infectious diseases and extend life expectancy. With people living to older ages, chronic conditions and diseases have become the primary threats to health and well-being in populations throughout the world. Accordingly, the scope of epidemiologic research now includes the study of acute and chronic diseases, as well as events, behaviors and conditions associated with health. With the expanded role of epidemiology have come considerable advances in epidemiologic study designs and methods. The purpose of this book is to present many of the current statistical methods being used. In the past 100 years, Janet Lane-Claypon, Alice Hamilton, and Wade- Hampton Frost pioneered the use of epidemiology as an analytical science, closely integrated with biology and medicine. While many physicians adopted epidemiology as a way to investigate disease etiology, this effort has included statisticians and scientists who have further contributed to the discipline by developing causal and statistical approaches. Sir Austin Bradford Hill pioneered the randomized clinical trial and Jerome Cornfield furthered its development. Many others, including Olli S. Miettinen, Joseph L. Fleiss, and Sander Greenland, have effectively applied statistical thinking to epidemiology. The book is divided into four sections: Basic Concepts in Epidemiology and Statistics, Epidemiologic Study Designs, Statistical Techniques and Epidemiologic Application, and Special Topics. Section I presents the fundamentals of epidemiology and statistics. Causal inference and issues related to obtaining precise, accurate, and valid measures and results are xvii _FMxx_00i_xviii.indd 17

18 xviii preface covered. Several cookbook techniques for estimating sample size and four probability sampling approaches are presented. Epidemiologic measures of disease frequency and association, along with concepts of disease surveillance and screening, complete this section. Section II begins with a chapter introducing the three general types of epidemiologic research (exploratory, descriptive, and analytic). Threats to study validity, in terms of findings related to chance, bias, and confounding are discussed, and ways to deal with these threats at the design and analysis phases of the study are described. Three subsequent chapters go into greater depth on descriptive, analytic, and experimental study designs, respectively. Section III covers statistical methods that are commonly employed in epidemiologic research. Methods are presented according to different types of epidemiologic data. Several applied examples are given, many of which include SAS code and output interpretation for assessing epidemiologic data. Section IV covers three additional topics where statistical methods are applied in epidemiologic research. Nonparametric statistical methods are presented, along with applications to epidemiologic data. Several data examples are given with corresponding SAS code. Epidemiologic research also often involves life table and survival analysis techniques. These topics make up the final two chapters of the book _FMxx_00i_xviii.indd 18