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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
  • Publsiher : Academic Press
  • Release : 06 October 2016
  • ISBN : 0081010087
  • Pages : 102 pages
  • Rating : 4/5 from 21 ratings
GET THIS BOOKAnalysis for Time to Event Data under Censoring and Truncation

Summary:
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


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 : 06 October 2016
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 : 29 June 2013
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


Survival Analysis Using S

Survival Analysis Using S
  • Author : Mara Tableman,Jong Sung Kim
  • Publisher : CRC Press
  • Release : 28 July 2003
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.


Handbook of Survival Analysis

Handbook of Survival Analysis
  • Author : John P. Klein,Hans C. van Houwelingen,Joseph G. Ibrahim,Thomas H. Scheike
  • Publisher : CRC Press
  • Release : 19 April 2016
GET THIS BOOKHandbook of Survival Analysis

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


The Statistical Analysis of Interval-censored Failure Time Data

The Statistical Analysis of Interval-censored Failure Time Data
  • Author : Jianguo Sun
  • Publisher : Springer
  • Release : 26 May 2007
GET THIS BOOKThe Statistical Analysis of Interval-censored Failure Time Data

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


Survival Analysis: State of the Art

Survival Analysis: State of the Art
  • Author : John P. Klein,Prem Goel
  • Publisher : Springer Science & Business Media
  • Release : 29 February 1992
GET THIS BOOKSurvival Analysis: State of the Art

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



Analysis of Doubly Truncated Data

Analysis of Doubly Truncated Data
  • Author : Achim Dörre,Takeshi Emura
  • Publisher : Springer
  • Release : 13 May 2019
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


Biostatistics

Biostatistics
  • Author : Wayne W. Daniel,Chad L. Cross
  • Publisher : Wiley
  • Release : 13 November 2018
GET THIS BOOKBiostatistics

The ability to analyze and interpret enormous amounts of data has become a prerequisite for success in allied healthcare and the health sciences. Now in its 11th edition, Biostatistics: A Foundation for Analysis in the Health Sciences continues to offer in-depth guidance toward biostatistical concepts, techniques, and practical applications in the modern healthcare setting. Comprehensive in scope yet detailed in coverage, this text helps students understand—and appropriately use—probability distributions, sampling distributions, estimation, hypothesis testing, variance analysis, regression, correlation


Introducing Survival and Event History Analysis

Introducing Survival and Event History Analysis
  • Author : Melinda Mills
  • Publisher : SAGE
  • Release : 19 January 2011
GET THIS BOOKIntroducing Survival and Event History Analysis

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,


Event History Analysis with R

Event History Analysis with R
  • Author : Göran Broström
  • Publisher : CRC Press
  • Release : 03 September 2018
GET THIS BOOKEvent History Analysis with R

With an emphasis on social science applications, Event History Analysis with R presents an introduction to survival and event history analysis using real-life examples. Keeping mathematical details to a minimum, the book covers key topics, including both discrete and continuous time data, parametric proportional hazards, and accelerated failure times. Features Introduces parametric proportional hazards models with baseline distributions like the Weibull, Gompertz, Lognormal, and Piecewise constant hazard distributions, in addition to traditional Cox regression Presents mathematical details as well as


Interval-Censored Time-to-Event Data

Interval-Censored Time-to-Event Data
  • Author : Ding-Geng (Din) Chen,Jianguo Sun,Karl E. Peace
  • Publisher : CRC Press
  • Release : 19 July 2012
GET THIS BOOKInterval-Censored Time-to-Event Data

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


Analysis of Survival Data with Dependent Censoring

Analysis of Survival Data with Dependent Censoring
  • Author : Takeshi Emura,Yi-Hau Chen
  • Publisher : Springer
  • Release : 05 April 2018
GET THIS BOOKAnalysis of Survival Data with Dependent Censoring

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 and Survival Analysis

Reliability and Survival Analysis
  • Author : Md. Rezaul Karim,M. Ataharul Islam
  • Publisher : Springer
  • Release : 09 August 2019
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


An Introduction to Survival Analysis Using Stata, Second Edition

An Introduction to Survival Analysis Using Stata, Second Edition
  • Author : Mario Cleves,William Gould,William W. Gould,Roberto Gutierrez,Yulia Marchenko
  • Publisher : Stata Press
  • Release : 15 May 2008
GET THIS BOOKAn Introduction to Survival Analysis Using Stata, Second Edition

"[This book] provides new researchers with the foundation for understanding the various approaches for analyzing time-to-event data. This book serves not only as a tutorial for those wishing to learn survival analysis but as a ... reference for experienced researchers ..."--Book jacket.