Emerging Topics In Modeling Interval Censored Survival Data

Author : Jianguo Sun,Ding-Geng Chen
Publisher : Springer Nature
Page : 322 pages
File Size : 55,8 Mb
Release : 2022-11-29
Category : Mathematics
ISBN : 9783031123665

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Emerging Topics in Modeling Interval-Censored Survival Data by Jianguo Sun,Ding-Geng Chen Pdf

This book primarily aims to discuss emerging topics in statistical methods and to booster research, education, and training to advance statistical modeling on interval-censored survival data. Commonly collected from public health and biomedical research, among other sources, interval-censored survival data can easily be mistaken for typical right-censored survival data, which can result in erroneous statistical inference due to the complexity of this type of data. The book invites a group of internationally leading researchers to systematically discuss and explore the historical development of the associated methods and their computational implementations, as well as emerging topics related to interval-censored data. It covers a variety of topics, including univariate interval-censored data, multivariate interval-censored data, clustered interval-censored data, competing risk interval-censored data, data with interval-censored covariates, interval-censored data from electric medical records, and misclassified interval-censored data. Researchers, students, and practitioners can directly make use of the state-of-the-art methods covered in the book to tackle their problems in research, education, training and consultation.

Author : Kris Bogaerts,Arnost Komarek,Emmanuel Lesaffre
Publisher : CRC Press
Page : 644 pages
File Size : 48,5 Mb
Release : 2017-11-20
Category : Mathematics
ISBN : 9781351643054

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Survival Analysis with Interval-Censored Data by Kris Bogaerts,Arnost Komarek,Emmanuel Lesaffre Pdf

Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R, SAS, and BUGS provides the reader with a practical introduction into the analysis of interval-censored survival times. Although many theoretical developments have appeared in the last fifty years, interval censoring is often ignored in practice. Many are unaware of the impact of inappropriately dealing with interval censoring. In addition, the necessary software is at times difficult to trace. This book fills in the gap between theory and practice. Features: -Provides an overview of frequentist as well as Bayesian methods. -Include a focus on practical aspects and applications. -Extensively illustrates the methods with examples using R, SAS, and BUGS. Full programs are available on a supplementary website. The authors: Kris Bogaerts is project manager at I-BioStat, KU Leuven. He received his PhD in science (statistics) at KU Leuven on the analysis of interval-censored data. He has gained expertise in a great variety of statistical topics with a focus on the design and analysis of clinical trials. Arnošt Komárek is associate professor of statistics at Charles University, Prague. His subject area of expertise covers mainly survival analysis with the emphasis on interval-censored data and classification based on longitudinal data. He is past chair of the Statistical Modelling Society and editor of Statistical Modelling: An International Journal. Emmanuel Lesaffre is professor of biostatistics at I-BioStat, KU Leuven. His research interests include Bayesian methods, longitudinal data analysis, statistical modelling, analysis of dental data, interval-censored data, misclassification issues, and clinical trials. He is the founding chair of the Statistical Modelling Society, past-president of the International Society for Clinical Biostatistics, and fellow of ISI and ASA.

Author : Ardo van den Hout
Publisher : CRC Press
Page : 257 pages
File Size : 43,7 Mb
Release : 2016-11-25
Category : Mathematics
ISBN : 9781466568419

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Multi-State Survival Models for Interval-Censored Data by Ardo van den Hout Pdf

Multi-State Survival Models for Interval-Censored Data introduces methods to describe stochastic processes that consist of transitions between states over time. It is targeted at researchers in medical statistics, epidemiology, demography, and social statistics. One of the applications in the book is a three-state process for dementia and survival in the older population. This process is described by an illness-death model with a dementia-free state, a dementia state, and a dead state. Statistical modelling of a multi-state process can investigate potential associations between the risk of moving to the next state and variables such as age, gender, or education. A model can also be used to predict the multi-state process. The methods are for longitudinal data subject to interval censoring. Depending on the definition of a state, it is possible that the time of the transition into a state is not observed exactly. However, when longitudinal data are available the transition time may be known to lie in the time interval defined by two successive observations. Such an interval-censored observation scheme can be taken into account in the statistical inference. Multi-state modelling is an elegant combination of statistical inference and the theory of stochastic processes. Multi-State Survival Models for Interval-Censored Data shows that the statistical modelling is versatile and allows for a wide range of applications.

Author : Jianguo Sun
Publisher : Springer
Page : 304 pages
File Size : 47,6 Mb
Release : 2007-05-26
Category : Mathematics
ISBN : 9780387371191

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The Statistical Analysis of Interval-censored Failure Time Data by Jianguo Sun Pdf

This book collects and unifies statistical models and methods that have been proposed for analyzing interval-censored failure time data. It provides the first comprehensive coverage of the topic of interval-censored data and complements the books on right-censored data. The focus of the book is on nonparametric and semiparametric inferences, but it also describes parametric and imputation approaches. This book provides an up-to-date reference for people who are conducting research on the analysis of interval-censored failure time data as well as for those who need to analyze interval-censored data to answer substantive questions.

Author : David Collett
Publisher : CRC Press
Page : 557 pages
File Size : 42,6 Mb
Release : 2023-05-31
Category : Medical
ISBN : 9781000863109

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Modelling Survival Data in Medical Research by David Collett Pdf

Hugely popular textbook on survival analysis for graduate students of statistics and biostatistics, mainly due to its accessibility and breadth of examples. This is a standard course on graduate programs in biostatistics and statistics, and this is one of the most popular textbooks. Updated with modern methods covering Bayesian survival analysis, joint models, and more.

Author : Ding-Geng (Din) Chen,Jianguo Sun,Karl E. Peace
Publisher : CRC Press
Page : 426 pages
File Size : 54,6 Mb
Release : 2012-07-19
Category : Mathematics
ISBN : 9781466504288

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Interval-Censored Time-to-Event Data by Ding-Geng (Din) Chen,Jianguo Sun,Karl E. Peace Pdf

Interval-Censored Time-to-Event Data: Methods and Applications collects the most recent techniques, models, and computational tools for interval-censored time-to-event data. Top biostatisticians from academia, biopharmaceutical industries, and government agencies discuss how these advances are impacting clinical trials and biomedical research.Divid

Author : David Collett
Publisher : CRC Press
Page : 413 pages
File Size : 42,9 Mb
Release : 2003-03-28
Category : Mathematics
ISBN : 9781584883258

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Modelling Survival Data in Medical Research, Second Edition by David Collett Pdf

Critically acclaimed and resoundingly popular in its first edition, Modelling Survival Data in Medical Research has been thoroughly revised and updated to reflect the many developments and advances--particularly in software--made in the field over the last 10 years. Now, more than ever, it provides an outstanding text for upper-level and graduate courses in survival analysis, biostatistics, and time-to-event analysis.The treatment begins with an introduction to survival analysis and a description of four studies that lead to survival data. Subsequent chapters then use those data sets and others to illustrate the various analytical techniques applicable to such data, including the Cox regression model, the Weibull proportional hazards model, and others. This edition features a more detailed treatment of topics such as parametric models, accelerated failure time models, and analysis of interval-censored data. The author also focuses the software section on the use of SAS, summarising the methods used by the software to generate its output and examining that output in detail. Profusely illustrated with examples and written in the author's trademark, easy-to-follow style, Modelling Survival Data in Medical Research, Second Edition is a thorough, practical guide to survival analysis that reflects current statistical practices.

Author : Kris Bogaerts,Arnošt Komárek,Emmanuel Lesaffre
Publisher : Unknown
Page : 588 pages
File Size : 50,9 Mb
Release : 2017
Category : MATHEMATICS
ISBN : 1315116944

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Survival Analysis with Interval-Censored Data by Kris Bogaerts,Arnošt Komárek,Emmanuel Lesaffre Pdf

"This book describes methods and software implementations for the analysis of interval-censored data. The authors present the theoretical background for all methods and apply the methods to real data sets. They also provide the R, SAS, and WinBUGS code for all the examples, enabling readers to modify the code and use the methods to solve their own practical problems. In addition, most of the data sets used in the text are available online."--Provided by publisher.

Author : D. Collett
Publisher : Unknown
Page : 391 pages
File Size : 48,8 Mb
Release : 2003
Category : MATHEMATICS
ISBN : 042925847X

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Modelling Survival Data in Medical Research by D. Collett Pdf

Survival analysis is an active field and many advances, particularly in software, have emerged over the last eight years. Modelling Survival Data in Medical Research, Second Edition updates and expands on the highly successful first edition, which was praised for its clarity, content, and broad-based accessibility. This edition presents the most current and useful modelling techniques in survival data analysis, including recent developments in model checking, parametric models, time-dependent variables, and interval censored data. For this edition, the author has focused the software sections.

Author : Torben Martinussen,Thomas H. Scheike
Publisher : Springer Science & Business Media
Page : 470 pages
File Size : 51,6 Mb
Release : 2007-11-24
Category : Medical
ISBN : 9780387339603

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Dynamic Regression Models for Survival Data by Torben Martinussen,Thomas H. Scheike Pdf

This book studies and applies modern flexible regression models for survival data with a special focus on extensions of the Cox model and alternative models with the aim of describing time-varying effects of explanatory variables. Use of the suggested models and methods is illustrated on real data examples, using the R-package timereg developed by the authors, which is applied throughout the book with worked examples for the data sets.

Author : John P. Klein,Hans C. van Houwelingen,Joseph G. Ibrahim,Thomas H. Scheike
Publisher : CRC Press
Page : 635 pages
File Size : 54,9 Mb
Release : 2016-04-19
Category : Mathematics
ISBN : 9781466555679

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Handbook of Survival Analysis by John P. Klein,Hans C. van Houwelingen,Joseph G. Ibrahim,Thomas H. Scheike Pdf

Handbook of Survival Analysis presents modern techniques and research problems in lifetime data analysis. This area of statistics deals with time-to-event data that is complicated by censoring and the dynamic nature of events occurring in time. With chapters written by leading researchers in the field, the handbook focuses on advances in survival analysis techniques, covering classical and Bayesian approaches. It gives a complete overview of the current status of survival analysis and should inspire further research in the field. Accessible to a wide range of readers, the book provides: An introduction to various areas in survival analysis for graduate students and novices A reference to modern investigations into survival analysis for more established researchers A text or supplement for a second or advanced course in survival analysis A useful guide to statistical methods for analyzing survival data experiments for practicing statisticians

Author : Daohai Yu
Publisher : Unknown
Page : 268 pages
File Size : 43,6 Mb
Release : 2000
Category : Electronic
ISBN : UOM:39015050175069

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Analysis of Dependent Interval-censored Time-to-event Data by Daohai Yu Pdf

Author : D.R. Cox,David Oakes
Publisher : CRC Press
Page : 216 pages
File Size : 50,6 Mb
Release : 1984-06-01
Category : Mathematics
ISBN : 041224490X

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Analysis of Survival Data by D.R. Cox,David Oakes Pdf

This monograph contains many ideas on the analysis of survival data to present a comprehensive account of the field. The value of survival analysis is not confined to medical statistics, where the benefit of the analysis of data on such factors as life expectancy and duration of periods of freedom from symptoms of a disease as related to a treatment applied individual histories and so on, is obvious. The techniques also find important applications in industrial life testing and a range of subjects from physics to econometrics. In the eleven chapters of the book the methods and applications of are discussed and illustrated by examples.

Author : Jerald F. Lawless
Publisher : John Wiley & Sons
Page : 662 pages
File Size : 54,6 Mb
Release : 2011-01-25
Category : Mathematics
ISBN : 9781118031254

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Statistical Models and Methods for Lifetime Data by Jerald F. Lawless Pdf

Praise for the First Edition "An indispensable addition to any serious collection on lifetime data analysis and . . . a valuable contribution to the statistical literature. Highly recommended . . ." -Choice "This is an important book, which will appeal to statisticians working on survival analysis problems." -Biometrics "A thorough, unified treatment of statistical models and methods used in the analysis of lifetime data . . . this is a highly competent and agreeable statistical textbook." -Statistics in Medicine The statistical analysis of lifetime or response time data is a key tool in engineering, medicine, and many other scientific and technological areas. This book provides a unified treatment of the models and statistical methods used to analyze lifetime data. Equally useful as a reference for individuals interested in the analysis of lifetime data and as a text for advanced students, Statistical Models and Methods for Lifetime Data, Second Edition provides broad coverage of the area without concentrating on any single field of application. Extensive illustrations and examples drawn from engineering and the biomedical sciences provide readers with a clear understanding of key concepts. New and expanded coverage in this edition includes: * Observation schemes for lifetime data * Multiple failure modes * Counting process-martingale tools * Both special lifetime data and general optimization software * Mixture models * Treatment of interval-censored and truncated data * Multivariate lifetimes and event history models * Resampling and simulation methodology

Author : Yuhlong Lio,Ding-Geng Chen,Hon Keung Tony Ng,Tzong-Ru Tsai
Publisher : Springer Nature
Page : 367 pages
File Size : 48,6 Mb
Release : 2022-08-01
Category : Mathematics
ISBN : 9783030886585

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Bayesian Inference and Computation in Reliability and Survival Analysis by Yuhlong Lio,Ding-Geng Chen,Hon Keung Tony Ng,Tzong-Ru Tsai Pdf

Bayesian analysis is one of the important tools for statistical modelling and inference. Bayesian frameworks and methods have been successfully applied to solve practical problems in reliability and survival analysis, which have a wide range of real world applications in medical and biological sciences, social and economic sciences, and engineering. In the past few decades, significant developments of Bayesian inference have been made by many researchers, and advancements in computational technology and computer performance has laid the groundwork for new opportunities in Bayesian computation for practitioners. Because these theoretical and technological developments introduce new questions and challenges, and increase the complexity of the Bayesian framework, this book brings together experts engaged in groundbreaking research on Bayesian inference and computation to discuss important issues, with emphasis on applications to reliability and survival analysis. Topics covered are timely and have the potential to influence the interacting worlds of biostatistics, engineering, medical sciences, statistics, and more. The included chapters present current methods, theories, and applications in the diverse area of biostatistical analysis. The volume as a whole serves as reference in driving quality global health research.