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Book Statistical Analysis of Interval censored and Truncated Survival Data

Download or read book Statistical Analysis of Interval censored and Truncated Survival Data written by Hee-Jeong Lim and published by . This book was released on 2001 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data from clinical trials and epidemiological studies are often incomplete due to interval censoring and truncation. In this thesis, we will discuss the statistical analysis of survival data with interval-censoring and truncation. First, we consider the problem of comparing two failure time distributions based on interval-censored data. We propose three classes of nonparametric test procedures, which include most existing methods as special cases. To evaluate and compare the proposed and existing tests and to draw a guideline for selecting an appropriate test for a given situation, an extensive simulation study is conducted. Secondly, we consider the problem of estimating a survival function when there exists a change point. To obtain the maximum likelihood estimator of a survival function in this case, an EM algorithm is developed when the survival function is completely unknown before the change point and known up to a vector of unknown parameters after the change point. We evaluate the performance of the proposed algorithm and illustrate it using a set of survival data arising from an AIDS study. Thirdly, we consider a regression analysis of survival data with interval-censored covariates. To estimate regression parameters, methods based on estimating equations are developed. An extensive simulation study is performed to evaluate the proposed method.

Book The Statistical Analysis of Interval censored Failure Time Data

Download or read book The Statistical Analysis of Interval censored Failure Time Data written by Jianguo Sun and published by Springer. This book was released on 2007-05-26 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Survival Analysis with Interval Censored Data

Download or read book Survival Analysis with Interval Censored Data written by Kris Bogaerts and published by CRC Press. This book was released on 2017-11-20 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Survival Analysis

    Book Details:
  • Author : John P. Klein
  • Publisher : Springer Science & Business Media
  • Release : 2013-06-29
  • ISBN : 1475727283
  • Pages : 508 pages

Download or read book Survival Analysis written by John P. Klein and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: Making complex methods more accessible to applied researchers without an advanced mathematical background, the authors present the essence of new techniques available, as well as classical techniques, and apply them to data. Practical suggestions for implementing the various methods are set off in a series of practical notes at the end of each section, while technical details of the derivation of the techniques are sketched in the technical notes. This book will thus be useful for investigators who need to analyse censored or truncated life time data, and as a textbook for a graduate course in survival analysis, the only prerequisite being a standard course in statistical methodology.

Book Interval Censored Time to Event Data

Download or read book Interval Censored Time to Event Data written by Ding-Geng (Din) Chen and published by CRC Press. This book was released on 2012-07-19 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Book Statistical Analysis of Interval censored Failure Time Data

Download or read book Statistical Analysis of Interval censored Failure Time Data written by Alicia Worrall and published by . This book was released on 2015 with total page 75 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, we will examine the statistical methods used in survival analysis applied to interval-censored failure time data. Interval-censored data is not widely used due to the fact that it is more difficult to work with. However, the same methods commonly used for random- censoring can be applied to interval-censoring as well. This includes finding the basic quantities, survival curves, regression analysis, Bayesian regression analysis and a comparison between interval-censored data and random-censored data.

Book Survival Analysis Using S

Download or read book Survival Analysis Using S written by Mara Tableman and published by CRC Press. This book was released on 2003-07-28 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Survival Analysis Using S: Analysis of Time-to-Event Data is designed as a text for a one-semester or one-quarter course in survival analysis for upper-level or graduate students in statistics, biostatistics, and epidemiology. Prerequisites are a standard pre-calculus first course in probability and statistics, and a course in applied linear regression models. No prior knowledge of S or R is assumed. A wide choice of exercises is included, some intended for more advanced students with a first course in mathematical statistics. The authors emphasize parametric log-linear models, while also detailing nonparametric procedures along with model building and data diagnostics. Medical and public health researchers will find the discussion of cut point analysis with bootstrap validation, competing risks and the cumulative incidence estimator, and the analysis of left-truncated and right-censored data invaluable. The bootstrap procedure checks robustness of cut point analysis and determines cut point(s). In a chapter written by Stephen Portnoy, censored regression quantiles - a new nonparametric regression methodology (2003) - is developed to identify important forms of population heterogeneity and to detect departures from traditional Cox models. By generalizing the Kaplan-Meier estimator to regression models for conditional quantiles, this methods provides a valuable complement to traditional Cox proportional hazards approaches.

Book Multi State Survival Models for Interval Censored Data

Download or read book Multi State Survival Models for Interval Censored Data written by Ardo van den Hout and published by CRC Press. This book was released on 2016-11-25 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Emerging Topics in Modeling Interval Censored Survival Data

Download or read book Emerging Topics in Modeling Interval Censored Survival Data written by Jianguo Sun and published by Springer Nature. This book was released on 2022-11-29 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Survival Analysis with Interval censored Data

Download or read book Survival Analysis with Interval censored Data written by Kris Bogaerts and published by . This book was released on 2018 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Handbook of Survival Analysis

Download or read book Handbook of Survival Analysis written by John P. Klein and published by CRC Press. This book was released on 2016-04-19 with total page 635 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Book Flexible Imputation of Missing Data  Second Edition

Download or read book Flexible Imputation of Missing Data Second Edition written by Stef van Buuren and published by CRC Press. This book was released on 2018-07-17 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, which are often not met in practice. Multiple imputation replaces each missing value by multiple plausible values. The variability between these replacements reflects our ignorance of the true (but missing) value. Each of the completed data set is then analyzed by standard methods, and the results are pooled to obtain unbiased estimates with correct confidence intervals. Multiple imputation is a general approach that also inspires novel solutions to old problems by reformulating the task at hand as a missing-data problem. This is the second edition of a popular book on multiple imputation, focused on explaining the application of methods through detailed worked examples using the MICE package as developed by the author. This new edition incorporates the recent developments in this fast-moving field. This class-tested book avoids mathematical and technical details as much as possible: formulas are accompanied by verbal statements that explain the formula in accessible terms. The book sharpens the reader’s intuition on how to think about missing data, and provides all the tools needed to execute a well-grounded quantitative analysis in the presence of missing data.

Book The Statistical Analysis of Failure Time Data

Download or read book The Statistical Analysis of Failure Time Data written by John D. Kalbfleisch and published by John Wiley & Sons. This book was released on 2011-01-25 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contains additional discussion and examples on left truncationas well as material on more general censoring and truncationpatterns. Introduces the martingale and counting process formulation swillbe in a new chapter. Develops multivariate failure time data in a separate chapterand extends the material on Markov and semi Markovformulations. Presents new examples and applications of data analysis.

Book Lifetime Data  Models in Reliability and Survival Analysis

Download or read book Lifetime Data Models in Reliability and Survival Analysis written by Nicholas P. Jewell and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical models and methods for lifetime and other time-to-event data are widely used in many fields, including medicine, the environmental sciences, actuarial science, engineering, economics, management, and the social sciences. For example, closely related statistical methods have been applied to the study of the incubation period of diseases such as AIDS, the remission time of cancers, life tables, the time-to-failure of engineering systems, employment duration, and the length of marriages. This volume contains a selection of papers based on the 1994 International Research Conference on Lifetime Data Models in Reliability and Survival Analysis, held at Harvard University. The conference brought together a varied group of researchers and practitioners to advance and promote statistical science in the many fields that deal with lifetime and other time-to-event-data. The volume illustrates the depth and diversity of the field. A few of the authors have published their conference presentations in the new journal Lifetime Data Analysis (Kluwer Academic Publishers).

Book Modelling Survival Data in Medical Research  Second Edition

Download or read book Modelling Survival Data in Medical Research Second Edition written by David Collett and published by CRC Press. This book was released on 2003-03-28 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Statistical Models and Methods for Lifetime Data

Download or read book Statistical Models and Methods for Lifetime Data written by Jerald F. Lawless and published by John Wiley & Sons. This book was released on 2011-01-25 with total page 662 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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