Analysis for Time to event Data Under Censoring and Truncation

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  • Publisher : Academic Press
  • Release : 01 October 2016
  • ISBN : 0128054808
  • Page : 96 pages
  • Rating : 4.5/5 from 103 voters

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"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 biasReviews existing works on survival analysis for truncated data, mainly focusing on the estimation of univariate and bivariate survival functionOffers a guideline for analyzing truncated survival data

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Analysis for Time-to-event Data Under Censoring and Truncation

Analysis for Time-to-event Data Under Censoring and Truncation
  • Author : Hongsheng Dai,Huan Wang
  • Publisher : Academic Press
  • Release Date : 2016-10-01
  • ISBN : 0128054808
GET THIS BOOKAnalysis for Time-to-event Data Under Censoring and Truncation

"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

Survival Analysis

Survival Analysis
  • Author : John P. Klein,Melvin L. Moeschberger
  • Publisher : Springer Science & Business Media
  • Release Date : 2006-05-17
  • ISBN : 9780387216454
GET THIS BOOKSurvival Analysis

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

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

Analysis for Time-to-Event Data under Censoring and Truncation
  • Author : Hongsheng Dai,Huan Wang
  • Publisher : Academic Press
  • Release Date : 2016-10-06
  • ISBN : 9780081010082
GET THIS BOOKAnalysis for Time-to-Event Data under Censoring and Truncation

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

Applied Categorical and Count Data Analysis

Applied Categorical and Count Data Analysis
  • Author : Wan Tang,Hua He,Xin M. Tu
  • Publisher : CRC Press
  • Release Date : 2023-04-06
  • ISBN : 9781000863970
GET THIS BOOKApplied Categorical and Count Data Analysis

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,

Survival Analysis Using S

Survival Analysis Using S
  • Author : Mara Tableman,Jong Sung Kim
  • Publisher : CRC Press
  • Release Date : 2003-07-28
  • ISBN : 9780203501412
GET THIS BOOKSurvival Analysis Using S

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.

Flexible Imputation of Missing Data, Second Edition

Flexible Imputation of Missing Data, Second Edition
  • Author : Stef van Buuren
  • Publisher : CRC Press
  • Release Date : 2018-07-17
  • ISBN : 9780429960352
GET THIS BOOKFlexible Imputation of Missing Data, Second Edition

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

Survival Analysis with Interval-Censored Data

Survival Analysis with Interval-Censored Data
  • Author : Kris Bogaerts,Arnost Komarek,Emmanuel Lesaffre
  • Publisher : CRC Press
  • Release Date : 2017-11-20
  • ISBN : 9781351643054
GET THIS BOOKSurvival Analysis with Interval-Censored Data

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.

Reliability and Survival Analysis

Reliability and Survival Analysis
  • Author : Md. Rezaul Karim,M. Ataharul Islam
  • Publisher : Springer
  • Release Date : 2019-08-09
  • ISBN : 9789811397769
GET THIS BOOKReliability and Survival Analysis

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

Advanced Survival Models

Advanced Survival Models
  • Author : Catherine Legrand
  • Publisher : CRC Press
  • Release Date : 2021-03-23
  • ISBN : 9780429622557
GET THIS BOOKAdvanced Survival Models

Survival data analysis is a very broad field of statistics, encompassing a large variety of methods used in a wide range of applications, and in particular in medical research. During the last twenty years, several extensions of "classical" survival models have been developed to address particular situations often encountered in practice. This book aims to gather in a single reference the most commonly used extensions, such as frailty models (in case of unobserved heterogeneity or clustered data), cure models (when

Encyclopedia of Quantitative Risk Analysis and Assessment

Encyclopedia of Quantitative Risk Analysis and Assessment
  • Author : Anonim
  • Publisher : John Wiley & Sons
  • Release Date : 2008-09-02
  • ISBN : 9780470035498
GET THIS BOOKEncyclopedia of Quantitative Risk Analysis and Assessment

Leading the way in this field, the Encyclopedia of Quantitative Risk Analysis and Assessment is the first publication to offer a modern, comprehensive and in-depth resource to the huge variety of disciplines involved. A truly international work, its coverage ranges across risk issues pertinent to life scientists, engineers, policy makers, healthcare professionals, the finance industry, the military and practising statisticians. Drawing on the expertise of world-renowned authors and editors in this field this title provides up-to-date material on drug safety,

Applied Survival Analysis

Applied Survival Analysis
  • Author : David W. Hosmer, Jr.,Stanley Lemeshow,Susanne May
  • Publisher : John Wiley & Sons
  • Release Date : 2011-09-23
  • ISBN : 9781118211588
GET THIS BOOKApplied Survival Analysis

THE MOST PRACTICAL, UP-TO-DATE GUIDE TO MODELLING AND ANALYZING TIME-TO-EVENT DATA—NOW IN A VALUABLE NEW EDITION Since publication of the first edition nearly a decade ago, analyses using time-to-event methods have increase considerably in all areas of scientific inquiry mainly as a result of model-building methods available in modern statistical software packages. However, there has been minimal coverage in the available literature to9 guide researchers, practitioners, and students who wish to apply these methods to health-related areas of study.

Survival Analysis

Survival Analysis
  • Author : John P. Klein,Melvin L. Moeschberger
  • Publisher : Springer Science & Business Media
  • Release Date : 2013-06-29
  • ISBN : 9781475727289
GET THIS BOOKSurvival Analysis

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

Analysis of Doubly Truncated Data

Analysis of Doubly Truncated Data
  • Author : Achim Dörre,Takeshi Emura
  • Publisher : Springer
  • Release Date : 2019-05-13
  • ISBN : 9789811362415
GET THIS BOOKAnalysis of Doubly Truncated Data

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

Machine Learning and Knowledge Discovery in Databases

Machine Learning and Knowledge Discovery in Databases
  • Author : Frank Hutter,Kristian Kersting,Jefrey Lijffijt,Isabel Valera
  • Publisher : Springer Nature
  • Release Date : 2021-02-24
  • ISBN : 9783030676643
GET THIS BOOKMachine Learning and Knowledge Discovery in Databases

The 5-volume proceedings, LNAI 12457 until 12461 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, which was held during September 14-18, 2020. The conference was planned to take place in Ghent, Belgium, but had to change to an online format due to the COVID-19 pandemic. The 232 full papers and 10 demo papers presented in this volume were carefully reviewed and selected for inclusion in the proceedings. The volumes are organized in topical sections as

Flexible Imputation of Missing Data, Second Edition

Flexible Imputation of Missing Data, Second Edition
  • Author : Stef van Buuren
  • Publisher : CRC Press
  • Release Date : 2018-07-17
  • ISBN : 9780429960345
GET THIS BOOKFlexible Imputation of Missing Data, Second Edition

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