Interval-Censored Time-to-Event Data: Methods and Applications

426 Pages·2012·3.11 MB·English

by  Ding-Geng (Din) Chen, Jianguo Sun, Karl E. Peace

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Statistics n
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Interval-Censored Time-to-Event Data: Methods and Applications
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collects the most recent techniques, models, and computational tools for l
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interval-censored time-to-event data. Top biostatisticians from academia, C Interval-Censored
biopharmaceutical industries, and government agencies discuss how
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these advances are impacting clinical trials and biomedical research. n
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Time-to-Event Data
Divided into three parts, the book begins with an overview of interval-
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censored data modeling, including nonparametric estimation, survival r
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functions, regression analysis, multivariate data analysis, competing
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risks analysis, and other models for interval-censored data. The next part Methods and Applications

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presents interval-censored methods for current status data, Bayesian
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semiparametric regression analysis of interval-censored data with m
monotone splines, Bayesian inferential models for interval-censored data,
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an estimator for identifying causal effect of treatment, and consistent -
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variance estimation for interval-censored data. In the final part, the
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contributors use Monte Carlo simulation to assess biases in progression- -
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free survival analysis as well as correct bias in interval-censored time-to-
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event applications. They also present adaptive decision-making methods
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to optimize the rapid treatment of stroke, explore practical issues in using
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weighted logrank tests, and describe how to use two R packages. t

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A practical guide for biomedical researchers, clinicians, biostatisticians,
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and graduate students in biostatistics, this volume covers the latest
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developments in the analysis and modeling of interval-censored time- a
to-event data. It shows how up-to-date statistical methods are used in
biopharmaceutical and public health applications.
Edited by
Ding-Geng (Din) Chen
P C
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a u Jianguo Sun
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Karl E. Peace
K14515
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Interval-Censored
Time-to-Event Data
Methods and Applications
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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

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Adaptive Design Methods in Clinical Trial Methodology
Clinical Trials, Second Edition Karl E. Peace and Ding-Geng (Din) Chen
Shein-Chung Chow and Mark Chang
Computational Methods in Biomedical
Adaptive Design Theory and Research
Implementation Using SAS and R Ravindra Khattree and Dayanand N. Naik
Mark Chang
Computational Pharmacokinetics
Advanced Bayesian Methods for Medical Anders Källén
Test Accuracy
Confidence Intervals for Proportions and
Lyle D. Broemeling
Related Measures of Effect Size
Advances in Clinical Trial Biostatistics Robert G. Newcombe
Nancy L. Geller
Controversial Statistical Issues in
Basic Statistics and Pharmaceutical Clinical Trials
Statistical Applications, Second Edition Shein-Chung Chow
James E. De Muth
Data and Safety Monitoring Committees
Bayesian Adaptive Methods for in Clinical Trials
Clinical Trials Jay Herson
Scott M. Berry, Bradley P. Carlin,
Design and Analysis of Animal Studies in
J. Jack Lee, and Peter Muller
Pharmaceutical Development
Bayesian Analysis Made Simple: An Excel Shein-Chung Chow and Jen-pei Liu
GUI for WinBUGS
Design and Analysis of Bioavailability and
Phil Woodward
Bioequivalence Studies, Third Edition
Bayesian Methods for Measures of Shein-Chung Chow and Jen-pei Liu
Agreement
Design and Analysis of Bridging Studies
Lyle D. Broemeling
Jen-pei Liu, Shein-Chung Chow,
Bayesian Missing Data Problems: EM, and Chin-Fu Hsiao
Data Augmentation and Noniterative
Design and Analysis of Clinical Trials with
Computation
Time-to-Event Endpoints
Ming T. Tan, Guo-Liang Tian,
Karl E. Peace
and Kai Wang Ng
Design and Analysis of Non-Inferiority
Bayesian Modeling in Bioinformatics
Trials
Dipak K. Dey, Samiran Ghosh,
Mark D. Rothmann, Brian L. Wiens,
and Bani K. Mallick
and Ivan S. F. Chan
Biostatistics: A Computing Approach
Difference Equations with Public Health
Stewart J. Anderson
Applications
Causal Analysis in Biomedicine and Lemuel A. Moyé and Asha Seth Kapadia
Epidemiology: Based on Minimal
DNA Methylation Microarrays:
Sufficient Causation
Experimental Design and Statistical
Mikel Aickin
Analysis
Clinical Trial Data Analysis using R Sun-Chong Wang and Arturas Petronis
Ding-Geng (Din) Chen and Karl E. Peace
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DNA Microarrays and Related Genomics Monte Carlo Simulation for the
Techniques: Design, Analysis, and Pharmaceutical Industry: Concepts,
Interpretation of Experiments Algorithms, and Case Studies
David B. Allison, Grier P. Page, Mark Chang
T. Mark Beasley, and Jode W. Edwards
Multiple Testing Problems in
Dose Finding by the Continual Pharmaceutical Statistics
Reassessment Method Alex Dmitrienko, Ajit C. Tamhane,
Ying Kuen Cheung and Frank Bretz
Elementary Bayesian Biostatistics Randomized Clinical Trials of
Lemuel A. Moyé Nonpharmacological Treatments
Isabelle Boutron, Philippe Ravaud, and
Frailty Models in Survival Analysis
David Moher
Andreas Wienke
Sample Size Calculations in Clinical
Generalized Linear Models: A Bayesian
Research, Second Edition
Perspective
Shein-Chung Chow, Jun Shao
Dipak K. Dey, Sujit K. Ghosh,
and Hansheng Wang
and Bani K. Mallick
Statistical Design and Analysis of
Handbook of Regression and Modeling:
Stability Studies
Applications for the Clinical and
Shein-Chung Chow
Pharmaceutical Industries
Daryl S. Paulson Statistical Evaluation of Diagnostic
Performance: Topics in ROC Analysis
Interval-Censored Time-to-Event Data:
Kelly H. Zou, Aiyi Liu, Andriy Bandos,
Methods and Applications
Lucila Ohno-Machado, and Howard Rockette
Ding-Geng (Din) Chen, Jianguo Sun,
and Karl E. Peace Statistical Methods for Clinical Trials
Mark X. Norleans
Joint Models for Longitudinal and Time-
to-Event Data: With Applications in R Statistics in Drug Research:
Dimitris Rizopoulos Methodologies and Recent
Developments
Measures of Interobserver Agreement
Shein-Chung Chow and Jun Shao
and Reliability, Second Edition
Mohamed M. Shoukri Statistics in the Pharmaceutical Industry,
Third Edition
Medical Biostatistics, Third Edition
Ralph Buncher and Jia-Yeong Tsay
A. Indrayan
Translational Medicine: Strategies and
Meta-Analysis in Medicine and Health
Statistical Methods
Policy
Dennis Cosmatos and Shein-Chung Chow
Dalene Stangl and Donald A. Berry
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Interval-Censored
Time-to-Event Data
Methods and Applications
Edited by
Ding-Geng (Din) Chen
Jianguo Sun
Karl E. Peace
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CRC Press
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To my parents and parents-in-law, who value higher education and hard
work, and to my wife Ke, my son John D. Chen, and my daughter Jenny K.
Chen, for their love and support.
Ding-Geng (Din) Chen
TomywifeXianghuanLi,andmysonsRyanandNicholasSun,fortheirlove,
patience, and support.
Jianguo Sun
TothememoryofmylatemotherElsieMaeCloudPeace,mylatewifeJiann-
Ping Hsu, and to my son Christopher K. Peace, daughter-in-law Ashley Hop-
kins Peace, and grandchildren Camden and Henry.
Karl E. Peace
TThhiiss ppaaggee iinntteennttiioonnaallllyy lleefftt bbllaannkk
Contents
List of Figures xvii
List of Tables xix
Preface xxi
List of Contributors xxv
I Introduction and Overview 1
1 Overview of Recent Developments for Interval-Censored
Data 3
Jianguo Sun and Junlong Li
1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2 More Introduction . . . . . . . . . . . . . . . . . . . . . . . . 6
1.3 Nonparametric Estimation . . . . . . . . . . . . . . . . . . . 9
1.4 Nonparametric Comparison of Survival Functions . . . . . . 12
1.5 Regression Analysis . . . . . . . . . . . . . . . . . . . . . . . 14
1.6 Analysis of Multivariate or Clustered Interval-Censored Data 17
1.7 Analysis of Competing Risks Interval-Censored Data . . . . 19
1.8 Other Topics and Concluding Remarks . . . . . . . . . . . . 20
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2 A Review of Various Models for Interval-Censored Data 29
Qiqing Yu and Yuting Hsu
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
ix