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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 644 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 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 181 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 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 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 435 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. Divided into three parts, the book begins with an overview of interval-censored data modeling, including nonparametric estimation, survival functions, regression analysis, multivariate data analysis, competing risks analysis, and other models for interval-censored data. The next part presents interval-censored methods for current status data, Bayesian semiparametric regression analysis of interval-censored data with monotone splines, Bayesian inferential models for interval-censored data, an estimator for identifying causal effect of treatment, and consistent variance estimation for interval-censored data. In the final part, the contributors use Monte Carlo simulation to assess biases in progression-free survival analysis as well as correct bias in interval-censored time-to-event applications. They also present adaptive decision making methods to optimize the rapid treatment of stroke, explore practical issues in using weighted logrank tests, and describe how to use two R packages. A practical guide for biomedical researchers, clinicians, biostatisticians, and graduate students in biostatistics, this volume covers the latest developments in the analysis and modeling of interval-censored time-to-event data. It shows how up-to-date statistical methods are used in biopharmaceutical and public health applications.

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 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 Survival analysis issues with interval censored data

Download or read book Survival analysis issues with interval censored data written by Ramon Oller Piqué and published by . This book was released on 2006 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Statistics for Censored Environmental Data Using Minitab and R

Download or read book Statistics for Censored Environmental Data Using Minitab and R written by Dennis R. Helsel and published by John Wiley & Sons. This book was released on 2012-02-01 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition " . . . an excellent addition to an upper-level undergraduate course on environmental statistics, and . . . a 'must-have' desk reference for environmental practitioners dealing with censored datasets." —Vadose Zone Journal Statistics for Censored Environmental Data Using Minitab® and R, Second Edition introduces and explains methods for analyzing and interpreting censored data in the environmental sciences. Adapting survival analysis techniques from other fields, the book translates well-established methods from other disciplines into new solutions for environmental studies. This new edition applies methods of survival analysis, including methods for interval-censored data to the interpretation of low-level contaminants in environmental sciences and occupational health. Now incorporating the freely available R software as well as Minitab® into the discussed analyses, the book features newly developed and updated material including: A new chapter on multivariate methods for censored data Use of interval-censored methods for treating true nondetects as lower than and separate from values between the detection and quantitation limits ("remarked data") A section on summing data with nondetects A newly written introduction that discusses invasive data, showing why substitution methods fail Expanded coverage of graphical methods for censored data The author writes in a style that focuses on applications rather than derivations, with chapters organized by key objectives such as computing intervals, comparing groups, and correlation. Examples accompany each procedure, utilizing real-world data that can be analyzed using the Minitab® and R software macros available on the book's related website, and extensive references direct readers to authoritative literature from the environmental sciences. Statistics for Censored Environmental Data Using Minitab® and R, Second Edition is an excellent book for courses on environmental statistics at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for??environmental professionals, biologists, and ecologists who focus on the water sciences, air quality, and soil science.

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 Statistical Methods for Survival Data Analysis

Download or read book Statistical Methods for Survival Data Analysis written by Elisa T. Lee and published by Wiley-Interscience. This book was released on 1992-05-07 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: Functions of survival time; Examples of survival data analysis; Nonparametric methods of estimating survival functions; Nonparametric methods for comparing survival distributions; Some well-known survival distributions and their applications; Graphical methods for sulvival distribution fitting and goodness-of-fit tests; Analytical estimation procedures for sulvival distributions; Parametric methods for comparing two survival distribution; Identification of prognostic factors related to survival time; Identification of risk factors related to dichotomous data; Planning and design of clinical trials (I); Planning and design of clinicL trials(II).

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 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 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 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 Model Evaluation and Variable Selection for Interval censored Data

Download or read book Model Evaluation and Variable Selection for Interval censored Data written by Tyler Cook and published by . This book was released on 2015 with total page 77 pages. Available in PDF, EPUB and Kindle. Book excerpt: Survival analysis is a popular area of statistics dealing with time-to-event data. This type of data can be seen in many disciplines, but it is perhaps most commonly encountered in medical studies. Doctors, for example, might be testing different treatments developed to prolong the lifetimes of cancer patients. Unfortunately, in practical problems such as clinical trials, there is often incomplete data thanks to patients dropping out of the study. This results in censoring, which is a special characteristic of survival data. There are many different types of censoring. This dissertation focuses on the analysis of interval-censored data, where the failure time is only known to belong to some interval of observation times. One problem that researchers face when analyzing survival data is how to handle the censoring distribution. It is often assumed that the observation process generating the censoring is independent of the event time of interest. Consequently, the observation process can effectively be ignored. However, this assumption is clearly not always realistic. Unfortunately, one cannot generally test for independent censoring without additional assumptions or information. Therefore, the researcher is faced with a choice between using methods designed for informative or noninformative censoring. Chapters 2 and 3 of this dissertation investigate the effectiveness of different methods developed for the analysis of informative case I and case II interval censored data under both types of censoring. Extensive simulation studies indicate that the methods produce unbiased results in the presence of both informative and noninformative censoring. The efficiency of the informative censoring methods is then compared with approaches created to handle noninformative censoring. The results of these simulation studies can provide guidelines for deciding between models when facing a practical problem where one is unsure about the dependence of the censoring distribution. Another important problem seen in survival analysis is determining the set of predictors that are significantly related with the failure time being studied. Variable selection has received substantial attention both in classical linear models as well as survival analysis. This is largely thanks to recent technological advances making it easier for researchers in biology to collect huge amounts of genetic data. For example, a researcher with access to gene expression levels for hundreds of genes is interested in identifying which of those genes can predict tumor development time in cancer patients. One must sift through the large number of genes in order to find the small set of significant genes that influence tumor growth. Several methods using penalized likelihood procedures have been proposed to perform parameter estimation and variable selection simultaneously. A number of these techniques have also been extended to the case of right-censored survival data, but little has been done in the context of interval-censoring. In chapter 4, we propose an imputation approach for variable selection of interval-censored data that utilizes these penalized likelihood procedures. This method uses imputation to create a new dataset of imputed exact failure times and right-censored observations. Variable selection can then be performed on the imputed dataset using any of the popular variable selection techniques created for right-censored data. Comprehensive simulation studies illustrate the effectiveness of this new approach. Also, this method is attractive due to how easy it is to implement, since it can take advantage of existing software for variable selection of right-censored data.

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