Analysis for Time to Event Data under Censoring and Truncation 1st Edition by Hongsheng Dai, Huan Wang ISBN 978-0128054802 0128054808

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Product details: 

ISBN 10:  0128054808

ISBN 13:  978-0128054802

Author: Hongsheng Dai,Huan Wang

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.

Table of contents: 

• Chapter 1: Introduction
  • 1.1 Introduction to the book
  • 1.2 Examples
  • 1.3 Brief review of survival analysis under truncation
  • 1.4 Preliminaries
• Chapter 2: Survival analysis for univariate truncated data
  • 2.1 Introduction
  • 2.2 Nonparametric estimation
  • 2.3 Linear Rank Statistics for umbrella alternative hypothesis
  • 2.4 Regression analysis for truncated and censored data
• Chapter 3: Bivariate estimation with truncated survival data
  • 3.1 Introduction
  • 3.2 Bivariate distributions
  • 3.3 Types of bivariate truncated survival data
  • 3.4 The inverse probability weighted estimator with only one censoring variable
  • 3.5 The transformation estimator
  • 3.6 Example
  • 3.7 Discussion
• Chapter 4: Accelerated failure time model for truncated and censored survival data
  • 4.1 Introduction
  • 4.2 WLS estimator for univariate LTRC data under AFT model
  • 4.3 AFT model for bivariate survival data under truncation and censoring
• Chapter 5: Recent advances for truncated survival data
  • 5.1 Linear transformation models
  • 5.2 Joint modelling of survival events and longitudinal data under random truncation
• Bibliography
• Index

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Tags: Hongsheng Dai, Huan Wang, Analysis for Time, Event Data, Censoring and Truncation