Bayesian Methods in Epidemiology

460 Pages·2013·6.766 MB·English

by  Lyle D. Broemeling

Statistics B
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Written by a biostatistics expert with over 20 years of experience in the
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field, Bayesian Methods in Epidemiology presents statistical methods
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used in epidemiology from a Bayesian viewpoint. It employs the software
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Bayesian
package WinBUGS to carry out the analyses and offers the code in the text i
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and for download online.
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The book examines study designs that investigate the association between
M Methods in
exposure to risk factors and the occurrence of disease. It covers intro-
ductory adjustment techniques to compare mortality between states and e
regression methods to study the association between various risk factors t
and disease, including logistic regression, simple and multiple linear re- h Epidemiology
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gression, categorical/ordinal regression, and nonlinear models. The text
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also introduces a Bayesian approach for the estimation of survival by life
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tables and illustrates other approaches to estimate survival, including a

parametric model based on the Weibull distribution and the Cox propor- i
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tional hazards (nonparametric) model. Using Bayesian methods to estimate

the lead time of the modality, the author explains how to screen for a dis-
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ease among individuals who do not exhibit any of its symptoms.
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Features i
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• Represents the only book that introduces epidemiology from a
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Bayesian viewpoint
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• Presents a Bayesian approach for disease screening
• Explains the most useful models in epidemiology, including survival i
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and regression models
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• Illustrates the techniques and models through real-world examples, o
including tumor registry data, a leukemia clinical trial, and health g
insurance data y
• Implements the analyses using WinBUGS
• Provides introductions to Bayesian inference for epidemiology and the
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use of WinBUGS in the appendices
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• Includes exercises and references at the end of each chapter o
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m
Lyle D. Broemeling
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K16074
K16074_Cover.indd 1 7/15/13 12:39 PM

Bayesian
Methods in
Epidemiology
Editor-in-Chief
Shein-Chung Chow, Ph.D.
Professor
Department of Biostatistics and Bioinformatics
Duke University School of Medicine
Durham, North Carolina
Series Editors
Byron Jones Jen-pei Liu
Biometrical Fellow Professor
Statistical Methodology Division of Biometry
Department of Agronomy
Integrated Information Sciences
National Taiwan University
Novartis Pharma AG
Taipei, Taiwan
Basel, Switzerland

Karl E. Peace Bruce W. Turnbull
Georgia Cancer Coalition Professor
Distinguished Cancer Scholar School of Operations Research
Senior Research Scientist and and Industrial Engineering
Professor of Biostatistics Cornell University
Jiann-Ping Hsu College of Public Health Ithaca, New York
Georgia Southern University
Statesboro, Georgia
Adaptive Design Methods in Biostatistics: A Computing Approach
Clinical Trials, Second Edition Stewart J. Anderson
Shein-Chung Chow and Mark Chang
Causal Analysis in Biomedicine and
Adaptive Design Theory and Epidemiology: Based on Minimal
Implementation Using SAS and R Sufficient Causation
Mark Chang Mikel Aickin
Advanced Bayesian Methods for Medical Clinical Trial Data Analysis using R
Test Accuracy Ding-Geng (Din) Chen and Karl E. Peace
Lyle D. Broemeling
Clinical Trial Methodology
Advances in Clinical Trial Biostatistics Karl E. Peace and Ding-Geng (Din) Chen
Nancy L. Geller
Computational Methods in Biomedical
Applied Meta-Analysis with R Research
Ding-Geng (Din) Chen and Karl E. Peace Ravindra Khattree and Dayanand N. Naik
Basic Statistics and Pharmaceutical Computational Pharmacokinetics
Statistical Applications, Second Edition Anders Källén
James E. De Muth
Confidence Intervals for Proportions and
Bayesian Adaptive Methods for Related Measures of Effect Size
Clinical Trials Robert G. Newcombe
Scott M. Berry, Bradley P. Carlin,
Controversial Statistical Issues in
J. Jack Lee, and Peter Muller
Clinical Trials
Bayesian Analysis Made Simple: An Excel Shein-Chung Chow
GUI for WinBUGS
Data and Safety Monitoring Committees
Phil Woodward
in Clinical Trials
Bayesian Methods for Measures of Jay Herson
Agreement
Design and Analysis of Animal Studies in
Lyle D. Broemeling
Pharmaceutical Development
Bayesian Methods in Epidemiology Shein-Chung Chow and Jen-pei Liu
Lyle D. Broemeling
Design and Analysis of Bioavailability and
Bayesian Methods in Health Economics Bioequivalence Studies, Third Edition
Gianluca Baio Shein-Chung Chow and Jen-pei Liu
Bayesian Missing Data Problems: EM, Design and Analysis of Bridging Studies
Data Augmentation and Noniterative Jen-pei Liu, Shein-Chung Chow,
Computation and Chin-Fu Hsiao
Ming T. Tan, Guo-Liang Tian,
Design and Analysis of Clinical Trials with
and Kai Wang Ng
Time-to-Event Endpoints
Bayesian Modeling in Bioinformatics Karl E. Peace
Dipak K. Dey, Samiran Ghosh,
Design and Analysis of Non-Inferiority
and Bani K. Mallick
Trials
Biosimilars: Design and Analysis of Mark D. Rothmann, Brian L. Wiens,
Follow-on Biologics and Ivan S. F. Chan
Shein-Chung Chow
Difference Equations with Public Health Multiple Testing Problems in
Applications Pharmaceutical Statistics
Lemuel A. Moyé and Asha Seth Kapadia Alex Dmitrienko, Ajit C. Tamhane,
and Frank Bretz
DNA Methylation Microarrays:
Experimental Design and Statistical Optimal Design for Nonlinear Response
Analysis Models
Sun-Chong Wang and Arturas Petronis Valerii V. Fedorov and Sergei L. Leonov
DNA Microarrays and Related Genomics Randomized Clinical Trials of
Techniques: Design, Analysis, and Nonpharmacological Treatments
Interpretation of Experiments Isabelle Boutron, Philippe Ravaud, and
David B. Allison, Grier P. Page, David Moher
T. Mark Beasley, and Jode W. Edwards
Randomized Phase II Cancer Clinical
Dose Finding by the Continual Trials
Reassessment Method Sin-Ho Jung
Ying Kuen Cheung
Sample Size Calculations in Clinical
Elementary Bayesian Biostatistics Research, Second Edition
Lemuel A. Moyé Shein-Chung Chow, Jun Shao
and Hansheng Wang
Frailty Models in Survival Analysis
Andreas Wienke Statistical Design and Analysis of
Stability Studies
Generalized Linear Models: A Bayesian
Shein-Chung Chow
Perspective
Dipak K. Dey, Sujit K. Ghosh, Statistical Evaluation of Diagnostic
and Bani K. Mallick Performance: Topics in ROC Analysis
Kelly H. Zou, Aiyi Liu, Andriy Bandos,
Handbook of Regression and Modeling:
Lucila Ohno-Machado, and Howard Rockette
Applications for the Clinical and
Pharmaceutical Industries Statistical Methods for Clinical Trials
Daryl S. Paulson Mark X. Norleans
Interval-Censored Time-to-Event Data: Statistics in Drug Research:
Methods and Applications Methodologies and Recent
Ding-Geng (Din) Chen, Jianguo Sun, Developments
and Karl E. Peace Shein-Chung Chow and Jun Shao
Joint Models for Longitudinal and Time- Statistics in the Pharmaceutical Industry,
to-Event Data: With Applications in R Third Edition
Dimitris Rizopoulos Ralph Buncher and Jia-Yeong Tsay
Measures of Interobserver Agreement Survival Analysis in Medicine and
and Reliability, Second Edition Genetics
Mohamed M. Shoukri Jialiang Li and Shuangge Ma
Medical Biostatistics, Third Edition Translational Medicine: Strategies and
A. Indrayan Statistical Methods
Dennis Cosmatos and Shein-Chung Chow
Meta-Analysis in Medicine and Health
Policy
Dalene Stangl and Donald A. Berry
Monte Carlo Simulation for the
Pharmaceutical Industry: Concepts,
Algorithms, and Case Studies
Mark Chang
Bayesian
Methods in
Epidemiology
Lyle D. Broemeling
Broemeling and Associates
Medical Lake, Washington, USA
CRC Press
Taylor & Francis Group
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Boca Raton, FL 33487-2742
© 2014 by Taylor & Francis Group, LLC
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Contents
1. Introduction to Bayesian Methods in Epidemiology ..............................1
1.1 Introduction ...........................................................................................1
1.2 Review of Statistical Methods in Epidemiology...............................1
1.3 Preview of the Book ..............................................................................4
1.3.1 Chapter 2: A Bayesian Perspective of Association
between Risk Exposure and Disease ....................................4
1.3.2 Chapter 3: Bayesian Methods of Adjustment of Data .........9
1.3.3 Chapter 4: Regression Methods for Adjustment ...............16
1.3.4 Chapter 5: A Bayesian Approach to Life Tables ................21
1.3.5 Chapter 6: A Bayesian Approach to Survival Analysis ....27
1.3.6 Chapter 7: Screening for Disease .........................................32
1.3.7 Chapter 8: Statistical Models for Epidemiology ................36
1.4 Preview of the Appendices ................................................................45
1.4.1 Appendix A: Introduction to Bayesian Statistics ..............45
1.4.2 Appendix B: Introduction to WinBUGS .............................47
1.5 Comments and Conclusions ..............................................................48
Exercises ..........................................................................................................48
References .......................................................................................................49
2. A Bayesian Perspective of Association between Risk
Exposure and Disease ..................................................................................53
2.1 Introduction .........................................................................................53
2.2 Incidence and Prevalence for Mortality and Morbidity ................54
2.3 Association between Risk and Disease in Cohort Studies ...........57
2.4 Retrospective Studies: Association between Risk and
Disease in Case–Control Studies ......................................................61
2.5 Cross-Sectional Studies ......................................................................65
2.6 Attributable Risk .................................................................................69
2.7 Comments and Conclusions ..............................................................73
Exercises ..........................................................................................................75
References .......................................................................................................80
3. Bayesian Methods of Adjustment of Data...............................................81
3.1 Introduction .........................................................................................81
3.2 Direct Adjustment of Data .................................................................82
3.3 Indirect Standardization Adjustment ..............................................90
3.3.1 Introduction ............................................................................90
3.3.2 Indirect Standardization .......................................................91
3.3.3 Bayesian Inferences for Indirect Adjustment ....................92
3.3.4 Example of Indirect Standardization ..................................93
© 2008 Taylor & Francis Group, LLC vii
viii Contents
3.4 Stratification and Association between Disease and
Risk Exposure ......................................................................................96
3.4.1 Introduction ............................................................................96
3.4.2 Interaction and Stratification ................................................97
3.4.3 An Example of Stratification ..............................................101
3.5 Mantel–Haenszel Estimator of Association ..................................103
3.6 Matching to Adjust Data in Case–Control Studies ......................107
3.7 Comments and Conclusions ............................................................109
Exercises ........................................................................................................110
References .....................................................................................................120
4. Regression Methods for Adjustment ......................................................121
4.1 Introduction .......................................................................................121
4.2 Logistic Regression ...........................................................................123
4.2.1 Introduction ..........................................................................123
4.2.2 An Example of Heart Disease ............................................124
4.2.3 An Example with Several Independent Variables ..........131
4.2.4 Goodness of Fit .....................................................................133
4.3 Linear Regression Models ...............................................................134
4.3.1 Introduction ..........................................................................134
4.3.2 Simple Linear Regression ...................................................135
4.3.3 Another Example of Simple Linear Regression ..............138
4.3.4 More on Multiple Linear Regression ................................141
4.3.5 An Example for Public Health ...........................................146
4.4 Weighted Regression ........................................................................149
4.5 Ordinal and Other Regression Models ..........................................156
4.6 Comments and Conclusions ............................................................156
Exercises ........................................................................................................158
References .....................................................................................................168
5. A Bayesian Approach to Life Tables .......................................................169
5.1 Introduction .......................................................................................169
5.2 Basic Life Table ..................................................................................170
5.2.1 Life Table Generalized ........................................................174
5.2.2 Another Generalization of the Life Table .........................177
5.3 Disease-Specific Life Tables .............................................................178
5.4 Life Tables for Medical Studies .......................................................181
5.4.1 Introduction ..........................................................................181
5.4.2 California Tumor Registry 1942–1963 ...............................183
5.5 Comparing Survival .........................................................................187
5.5.1 Introduction ..........................................................................187
5.5.2 Direct Bayesian Approach for Comparison of Survival ...188
5.5.3 Indirect Bayesian Comparison of Survival ......................190
5.5.3.1 Introduction ..........................................................190
5.5.3.2 Mantel–Haenszel Odds Ratio .............................191
© 2008 Taylor & Francis Group, LLC