Analysis For Time To Event Data Under Censoring And Truncation

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Analysis for Time-to-Event Data under Censoring and Truncation

Hongsheng Dai,Huan Wang
Analysis for Time to Event Data under Censoring and Truncation Book PDF

Author : Hongsheng Dai,Huan Wang
Publisher : Academic Press
Page : 0 pages
File Size : 52,7 Mb
Release : 2016-09-27
Category : Mathematics
ISBN : 0128054808

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Analysis for Time-to-Event Data under Censoring and Truncation by Hongsheng Dai,Huan Wang Pdf

Survival Analysis for Bivariate Truncated Data provides readers with a comprehensive review on the existing works on survival analysis for truncated data, mainly focusing on the estimation of univariate and bivariate survival function. The most distinguishing feature of survival data is known as censoring, which occurs when the survival time can only be exactly observed within certain time intervals. A second feature is truncation, which is often deliberate and usually due to selection bias in the study design. Truncation presents itself in different ways. For example, left truncation, which is often due to a so-called late entry bias, occurs when individuals enter a study at a certain age and are followed from this delayed entry time. Right truncation arises when only individuals who experienced the event of interest before a certain time point can be observed. Analyzing truncated survival data without considering the potential selection bias may lead to seriously biased estimates of the time to event of interest and the impact of risk factors.

Analysis for Time-to-Event Data under Censoring and Truncation

Hongsheng Dai,Huan Wang
Analysis for Time to Event Data under Censoring and Truncation Book PDF

Author : Hongsheng Dai,Huan Wang
Publisher : Academic Press
Page : 102 pages
File Size : 49,6 Mb
Release : 2016-10-06
Category : Mathematics
ISBN : 9780081010082

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Analysis for Time-to-Event Data under Censoring and Truncation by Hongsheng Dai,Huan Wang Pdf

Survival Analysis for Bivariate Truncated Data provides readers with a comprehensive review on the existing works on survival analysis for truncated data, mainly focusing on the estimation of univariate and bivariate survival function. The most distinguishing feature of survival data is known as censoring, which occurs when the survival time can only be exactly observed within certain time intervals. A second feature is truncation, which is often deliberate and usually due to selection bias in the study design. Truncation presents itself in different ways. For example, left truncation, which is often due to a so-called late entry bias, occurs when individuals enter a study at a certain age and are followed from this delayed entry time. Right truncation arises when only individuals who experienced the event of interest before a certain time point can be observed. Analyzing truncated survival data without considering the potential selection bias may lead to seriously biased estimates of the time to event of interest and the impact of risk factors. Assists statisticians, epidemiologists, medical researchers, and actuaries who need to understand the mechanism of selection bias Reviews existing works on survival analysis for truncated data, mainly focusing on the estimation of univariate and bivariate survival function Offers a guideline for analyzing truncated survival data

Survival Analysis

John P. Klein,Melvin L. Moeschberger
Survival Analysis Book PDF

Author : John P. Klein,Melvin L. Moeschberger
Publisher : Springer Science & Business Media
Page : 538 pages
File Size : 40,8 Mb
Release : 2006-05-17
Category : Medical
ISBN : 9780387216454

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Survival Analysis by John P. Klein,Melvin L. Moeschberger Pdf

Applied statisticians in many fields must frequently analyze time to event data. While the statistical tools presented in this book are applicable to data from medicine, biology, public health, epidemiology, engineering, economics, and demography, the focus here is on applications of the techniques to biology and medicine. The analysis of survival experiments is complicated by issues of censoring, where an individual's life length is known to occur only in a certain period of time, and by truncation, where individuals enter the study only if they survive a sufficient length of time or individuals are included in the study only if the event has occurred by a given date. The use of counting process methodology has allowed for substantial advances in the statistical theory to account for censoring and truncation in survival experiments. This book makes these complex methods more accessible to applied researchers without an advanced mathematical background. The authors present the essence of these techniques, as well as classical techniques not based on counting processes, 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. Technical details of the derivation of the techniques are sketched in a series of Technical Notes. This book will be useful for investigators who need to analyze censored or truncated life time data, and as a textbook for a graduate course in survival analysis. The prerequisite is a standard course in statistical methodology.

Survival Analysis Using S

Mara Tableman,Jong Sung Kim
Survival Analysis Using S Book PDF

Author : Mara Tableman,Jong Sung Kim
Publisher : CRC Press
Page : 277 pages
File Size : 54,7 Mb
Release : 2003-07-28
Category : Mathematics
ISBN : 9780203501412

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Survival Analysis Using S by Mara Tableman,Jong Sung Kim Pdf

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.

Flexible Imputation of Missing Data, Second Edition

Stef van Buuren
Flexible Imputation of Missing Data Second Edition Book PDF

Author : Stef van Buuren
Publisher : CRC Press
Page : 444 pages
File Size : 51,8 Mb
Release : 2018-07-17
Category : Mathematics
ISBN : 9780429960352

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Flexible Imputation of Missing Data, Second Edition by Stef van Buuren Pdf

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.

The Statistical Analysis of Interval-censored Failure Time Data

Jianguo Sun
The Statistical Analysis of Interval censored Failure Time Data Book PDF

Author : Jianguo Sun
Publisher : Springer
Page : 304 pages
File Size : 52,5 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.

The Statistical Analysis of Failure Time Data

John D. Kalbfleisch,Ross L. Prentice
The Statistical Analysis of Failure Time Data Book PDF

Author : John D. Kalbfleisch,Ross L. Prentice
Publisher : John Wiley & Sons
Page : 462 pages
File Size : 51,6 Mb
Release : 2011-01-25
Category : Mathematics
ISBN : 9781118031230

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The Statistical Analysis of Failure Time Data by John D. Kalbfleisch,Ross L. Prentice Pdf

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.

Reliability and Survival Analysis

Md. Rezaul Karim,M. Ataharul Islam
Reliability and Survival Analysis Book PDF

Author : Md. Rezaul Karim,M. Ataharul Islam
Publisher : Springer
Page : 252 pages
File Size : 47,5 Mb
Release : 2019-08-09
Category : Medical
ISBN : 9789811397769

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Reliability and Survival Analysis by Md. Rezaul Karim,M. Ataharul Islam Pdf

This book presents and standardizes statistical models and methods that can be directly applied to both reliability and survival analysis. These two types of analysis are widely used in many fields, including engineering, management, medicine, actuarial science, the environmental sciences, and the life sciences. Though there are a number of books on reliability analysis and a handful on survival analysis, there are virtually no books on both topics and their overlapping concepts. Offering an essential textbook, this book will benefit students, researchers, and practitioners in reliability and survival analysis, reliability engineering, biostatistics, and the biomedical sciences.

Survival Analysis: State of the Art

John P. Klein,P.K. Goel
Survival Analysis State of the Art Book PDF

Author : John P. Klein,P.K. Goel
Publisher : Springer Science & Business Media
Page : 446 pages
File Size : 43,6 Mb
Release : 2013-03-09
Category : Mathematics
ISBN : 9789401579834

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Survival Analysis: State of the Art by John P. Klein,P.K. Goel Pdf

Survival analysis is a highly active area of research with applications spanning the physical, engineering, biological, and social sciences. In addition to statisticians and biostatisticians, researchers in this area include epidemiologists, reliability engineers, demographers and economists. The economists survival analysis by the name of duration analysis and the analysis of transition data. We attempted to bring together leading researchers, with a common interest in developing methodology in survival analysis, at the NATO Advanced Research Workshop. The research works collected in this volume are based on the presentations at the Workshop. Analysis of survival experiments is complicated by issues of censoring, where only partial observation of an individual's life length is available and left truncation, where individuals enter the study group if their life lengths exceed a given threshold time. Application of the theory of counting processes to survival analysis, as developed by the Scandinavian School, has allowed for substantial advances in the procedures for analyzing such experiments. The increased use of computer intensive solutions to inference problems in survival analysis~ in both the classical and Bayesian settings, is also evident throughout the volume. Several areas of research have received special attention in the volume.

Analysis of Survival Data with Dependent Censoring

Takeshi Emura,Yi-Hau Chen
Analysis of Survival Data with Dependent Censoring Book PDF

Author : Takeshi Emura,Yi-Hau Chen
Publisher : Springer
Page : 84 pages
File Size : 46,5 Mb
Release : 2018-04-05
Category : Medical
ISBN : 9789811071645

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Analysis of Survival Data with Dependent Censoring by Takeshi Emura,Yi-Hau Chen Pdf

This book introduces readers to copula-based statistical methods for analyzing survival data involving dependent censoring. Primarily focusing on likelihood-based methods performed under copula models, it is the first book solely devoted to the problem of dependent censoring. The book demonstrates the advantages of the copula-based methods in the context of medical research, especially with regard to cancer patients’ survival data. Needless to say, the statistical methods presented here can also be applied to many other branches of science, especially in reliability, where survival analysis plays an important role. The book can be used as a textbook for graduate coursework or a short course aimed at (bio-) statisticians. To deepen readers’ understanding of copula-based approaches, the book provides an accessible introduction to basic survival analysis and explains the mathematical foundations of copula-based survival models.

Applied Categorical and Count Data Analysis

Wan Tang,Hua He,Xin M. Tu
Applied Categorical and Count Data Analysis Book PDF

Author : Wan Tang,Hua He,Xin M. Tu
Publisher : CRC Press
Page : 395 pages
File Size : 53,5 Mb
Release : 2023-04-06
Category : Mathematics
ISBN : 9781000863970

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Applied Categorical and Count Data Analysis by Wan Tang,Hua He,Xin M. Tu Pdf

Developed from the authors’ graduate-level biostatistics course, Applied Categorical and Count Data Analysis, Second Edition explains how to perform the statistical analysis of discrete data, including categorical and count outcomes. The authors have been teaching categorical data analysis courses at the University of Rochester and Tulane University for more than a decade. This book embodies their decade-long experience and insight in teaching and applying statistical models for categorical and count data. The authors describe the basic ideas underlying each concept, model, and approach to give readers a good grasp of the fundamentals of the methodology without relying on rigorous mathematical arguments. The second edition covers classic concepts and popular topics, such as contingency tables, logistic regression models, and Poisson regression models, along with modern areas that include models for zero-modified count outcomes, parametric and semiparametric longitudinal data analysis, reliability analysis, and methods for dealing with missing values. As in the first edition, R, SAS, SPSS, and Stata programming codes are provided for all the examples, enabling readers to immediately experiment with the data in the examples and even adapt or extend the codes to fit data from their own studies. Designed for a one-semester course for graduate and senior undergraduate students in biostatistics, this self-contained text is also suitable as a self-learning guide for biomedical and psychosocial researchers. It will help readers analyze data with discrete variables in a wide range of biomedical and psychosocial research fields. Features: Describes the basic ideas underlying each concept and model Includes R, SAS, SPSS and Stata programming codes for all the examples Features significantly expanded Chapters 4, 5, and 8 (Chapters 4-6, and 9 in the second edition Expands discussion for subtle issues in longitudinal and clustered data analysis such as time varying covariates and comparison of generalized linear mixed-effect models with GEE

Applied Survival Analysis Using R

Dirk F. Moore
Applied Survival Analysis Using R Book PDF

Author : Dirk F. Moore
Publisher : Springer
Page : 226 pages
File Size : 47,6 Mb
Release : 2016-05-11
Category : Medical
ISBN : 9783319312453

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Applied Survival Analysis Using R by Dirk F. Moore Pdf

Applied Survival Analysis Using R covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using R as a vehicle. Survival data, where the primary outcome is time to a specific event, arise in many areas of biomedical research, including clinical trials, epidemiological studies, and studies of animals. Many survival methods are extensions of techniques used in linear regression and categorical data, while other aspects of this field are unique to survival data. This text employs numerous actual examples to illustrate survival curve estimation, comparison of survivals of different groups, proper accounting for censoring and truncation, model variable selection, and residual analysis. Because explaining survival analysis requires more advanced mathematics than many other statistical topics, this book is organized with basic concepts and most frequently used procedures covered in earlier chapters, with more advanced topics near the end and in the appendices. A background in basic linear regression and categorical data analysis, as well as a basic knowledge of calculus and the R system, will help the reader to fully appreciate the information presented. Examples are simple and straightforward while still illustrating key points, shedding light on the application of survival analysis in a way that is useful for graduate students, researchers, and practitioners in biostatistics.

Counting Processes and Survival Analysis

Thomas R. Fleming,David P. Harrington
Counting Processes and Survival Analysis Book PDF

Author : Thomas R. Fleming,David P. Harrington
Publisher : John Wiley & Sons
Page : 454 pages
File Size : 41,8 Mb
Release : 2011-09-20
Category : Mathematics
ISBN : 9781118150665

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Counting Processes and Survival Analysis by Thomas R. Fleming,David P. Harrington Pdf

The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "The book is a valuable completion of the literature in this field. It is written in an ambitious mathematical style and can be recommended to statisticians as well as biostatisticians." -Biometrische Zeitschrift "Not many books manage to combine convincingly topics from probability theory over mathematical statistics to applied statistics. This is one of them. The book has other strong points to recommend it: it is written with meticulous care, in a lucid style, general results being illustrated by examples from statistical theory and practice, and a bunch of exercises serve to further elucidate and elaborate on the text." -Mathematical Reviews "This book gives a thorough introduction to martingale and counting process methods in survival analysis thereby filling a gap in the literature." -Zentralblatt für Mathematik und ihre Grenzgebiete/Mathematics Abstracts "The authors have performed a valuable service to researchers in providing this material in [a] self-contained and accessible form. . . This text [is] essential reading for the probabilist or mathematical statistician working in the area of survival analysis." -Short Book Reviews, International Statistical Institute Counting Processes and Survival Analysis explores the martingale approach to the statistical analysis of counting processes, with an emphasis on the application of those methods to censored failure time data. This approach has proven remarkably successful in yielding results about statistical methods for many problems arising in censored data. A thorough treatment of the calculus of martingales as well as the most important applications of these methods to censored data is offered. Additionally, the book examines classical problems in asymptotic distribution theory for counting process methods and newer methods for graphical analysis and diagnostics of censored data. Exercises are included to provide practice in applying martingale methods and insight into the calculus itself.

Analysis of Doubly Truncated Data

Achim Dörre,Takeshi Emura
Analysis of Doubly Truncated Data Book PDF

Author : Achim Dörre,Takeshi Emura
Publisher : Springer
Page : 109 pages
File Size : 55,9 Mb
Release : 2019-05-13
Category : Mathematics
ISBN : 9789811362415

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Analysis of Doubly Truncated Data by Achim Dörre,Takeshi Emura Pdf

This book introduces readers to statistical methodologies used to analyze doubly truncated data. The first book exclusively dedicated to the topic, it provides likelihood-based methods, Bayesian methods, non-parametric methods, and linear regression methods. These procedures can be used to effectively analyze continuous data, especially survival data arising in biostatistics and economics. Because truncation is a phenomenon that is often encountered in non-experimental studies, the methods presented here can be applied to many branches of science. The book provides R codes for most of the statistical methods, to help readers analyze their data. Given its scope, the book is ideally suited as a textbook for students of statistics, mathematics, econometrics, and other fields.

Introducing Survival and Event History Analysis

Melinda Mills
Introducing Survival and Event History Analysis Book PDF

Author : Melinda Mills
Publisher : SAGE
Page : 301 pages
File Size : 43,6 Mb
Release : 2011-01-19
Category : Social Science
ISBN : 9781848601024

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Introducing Survival and Event History Analysis by Melinda Mills Pdf

This book is an accessible, practical and comprehensive guide for researchers from multiple disciplines including biomedical, epidemiology, engineering and the social sciences. Written for accessibility, this book will appeal to students and researchers who want to understand the basics of survival and event history analysis and apply these methods without getting entangled in mathematical and theoretical technicalities. Inside, readers are offered a blueprint for their entire research project from data preparation to model selection and diagnostics. Engaging, easy to read, functional and packed with enlightening examples, ‘hands-on’ exercises, conversations with key scholars and resources for both students and instructors, this text allows researchers to quickly master advanced statistical techniques. It is written from the perspective of the ‘user’, making it suitable as both a self-learning tool and graduate-level textbook. Also included are up-to-date innovations in the field, including advancements in the assessment of model fit, unobserved heterogeneity, recurrent events and multilevel event history models. Practical instructions are also included for using the statistical programs of R, STATA and SPSS, enabling readers to replicate the examples described in the text.