Taylor & Francis GroupTaylor & Francis Group
Search all titles
  • Login
  • Hi, User  
    • Your Account
    • Logout
  • Search all titles
  • Search all collections
Interval-Censored Time-to-Event Data
loading
Interval-Censored Time-to-Event Data

Methods and Applications

Interval-Censored Time-to-Event Data

Methods and Applications

Edited ByDing-Geng (Din) Chen, Jianguo Sun, Karl E. Peace
Edition 1st Edition
First Published 2012
eBook Published 19 July 2012
Pub. location New York
Imprint Chapman and Hall/CRC
DOIhttps://doi.org/10.1201/b12290
Pages 434 pages
eBook ISBN 9781466504288
SubjectsBioscience, Medicine, Dentistry, Nursing & Allied Health
Get Citation

Get Citation

Chen, D.G. (Ed.), Sun, J. (Ed.), Peace, K. (Ed.). (2013). Interval-Censored Time-to-Event Data. New York: Chapman and Hall/CRC, https://doi.org/10.1201/b12290
ABOUT THIS BOOK

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

TABLE OF CONTENTS
part I|2 pages
I Introduction and Overview
chapter 1|26 pages
Overview of Recent Developments for Interval-Censored Data
View abstract
chapter 2|14 pages
A Review of Various Models for Interval-Censored Data
View abstract
part II|2 pages
II Methodology
chapter 3|46 pages
Current Status Data in the Twenty-First Century
View abstract
chapter 4|22 pages
Regression Analysis for Current Status Data
View abstract
chapter 5|36 pages
Statistical Analysis of Dependent Current Status Data
View abstract
chapter 6|18 pages
Bayesian Semiparametric Regression Analysis of Interval- Censored Data with Monotone Splines
View abstract
chapter 7|30 pages
Bayesian Inference of Interval-Censored Survival Data
View abstract
chapter 8|36 pages
Targeted Minimum Loss–Based Estimation of a Causal Effect Using Interval-Censored Time-to-Event Data
View abstract
chapter 9|36 pages
Consistent Variance Estimation in Interval-Censored Data
View abstract
part III|2 pages
III Applications and Related Software
chapter 10|40 pages
Bias Assessment in Progression-Free Survival Analysis
View abstract
chapter 11|18 pages
Bias and Its Remedy in Interval-Censored Time-to-Event Applications
View abstract
chapter 12|16 pages
Adaptive Decision Making Based on Interval-Censored of Stroke
View abstract
chapter 13|32 pages
Practical Issues on Using Weighted Logrank Tests
View abstract
chapter 14|21 pages
glrt – New R Package for Analyzing Interval-Censored Sur- vival Data
View abstract

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

TABLE OF CONTENTS
part I|2 pages
I Introduction and Overview
chapter 1|26 pages
Overview of Recent Developments for Interval-Censored Data
View abstract
chapter 2|14 pages
A Review of Various Models for Interval-Censored Data
View abstract
part II|2 pages
II Methodology
chapter 3|46 pages
Current Status Data in the Twenty-First Century
View abstract
chapter 4|22 pages
Regression Analysis for Current Status Data
View abstract
chapter 5|36 pages
Statistical Analysis of Dependent Current Status Data
View abstract
chapter 6|18 pages
Bayesian Semiparametric Regression Analysis of Interval- Censored Data with Monotone Splines
View abstract
chapter 7|30 pages
Bayesian Inference of Interval-Censored Survival Data
View abstract
chapter 8|36 pages
Targeted Minimum Loss–Based Estimation of a Causal Effect Using Interval-Censored Time-to-Event Data
View abstract
chapter 9|36 pages
Consistent Variance Estimation in Interval-Censored Data
View abstract
part III|2 pages
III Applications and Related Software
chapter 10|40 pages
Bias Assessment in Progression-Free Survival Analysis
View abstract
chapter 11|18 pages
Bias and Its Remedy in Interval-Censored Time-to-Event Applications
View abstract
chapter 12|16 pages
Adaptive Decision Making Based on Interval-Censored of Stroke
View abstract
chapter 13|32 pages
Practical Issues on Using Weighted Logrank Tests
View abstract
chapter 14|21 pages
glrt – New R Package for Analyzing Interval-Censored Sur- vival Data
View abstract
CONTENTS
ABOUT THIS BOOK

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

TABLE OF CONTENTS
part I|2 pages
I Introduction and Overview
chapter 1|26 pages
Overview of Recent Developments for Interval-Censored Data
View abstract
chapter 2|14 pages
A Review of Various Models for Interval-Censored Data
View abstract
part II|2 pages
II Methodology
chapter 3|46 pages
Current Status Data in the Twenty-First Century
View abstract
chapter 4|22 pages
Regression Analysis for Current Status Data
View abstract
chapter 5|36 pages
Statistical Analysis of Dependent Current Status Data
View abstract
chapter 6|18 pages
Bayesian Semiparametric Regression Analysis of Interval- Censored Data with Monotone Splines
View abstract
chapter 7|30 pages
Bayesian Inference of Interval-Censored Survival Data
View abstract
chapter 8|36 pages
Targeted Minimum Loss–Based Estimation of a Causal Effect Using Interval-Censored Time-to-Event Data
View abstract
chapter 9|36 pages
Consistent Variance Estimation in Interval-Censored Data
View abstract
part III|2 pages
III Applications and Related Software
chapter 10|40 pages
Bias Assessment in Progression-Free Survival Analysis
View abstract
chapter 11|18 pages
Bias and Its Remedy in Interval-Censored Time-to-Event Applications
View abstract
chapter 12|16 pages
Adaptive Decision Making Based on Interval-Censored of Stroke
View abstract
chapter 13|32 pages
Practical Issues on Using Weighted Logrank Tests
View abstract
chapter 14|21 pages
glrt – New R Package for Analyzing Interval-Censored Sur- vival Data
View abstract

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

TABLE OF CONTENTS
part I|2 pages
I Introduction and Overview
chapter 1|26 pages
Overview of Recent Developments for Interval-Censored Data
View abstract
chapter 2|14 pages
A Review of Various Models for Interval-Censored Data
View abstract
part II|2 pages
II Methodology
chapter 3|46 pages
Current Status Data in the Twenty-First Century
View abstract
chapter 4|22 pages
Regression Analysis for Current Status Data
View abstract
chapter 5|36 pages
Statistical Analysis of Dependent Current Status Data
View abstract
chapter 6|18 pages
Bayesian Semiparametric Regression Analysis of Interval- Censored Data with Monotone Splines
View abstract
chapter 7|30 pages
Bayesian Inference of Interval-Censored Survival Data
View abstract
chapter 8|36 pages
Targeted Minimum Loss–Based Estimation of a Causal Effect Using Interval-Censored Time-to-Event Data
View abstract
chapter 9|36 pages
Consistent Variance Estimation in Interval-Censored Data
View abstract
part III|2 pages
III Applications and Related Software
chapter 10|40 pages
Bias Assessment in Progression-Free Survival Analysis
View abstract
chapter 11|18 pages
Bias and Its Remedy in Interval-Censored Time-to-Event Applications
View abstract
chapter 12|16 pages
Adaptive Decision Making Based on Interval-Censored of Stroke
View abstract
chapter 13|32 pages
Practical Issues on Using Weighted Logrank Tests
View abstract
chapter 14|21 pages
glrt – New R Package for Analyzing Interval-Censored Sur- vival Data
View abstract
ABOUT THIS BOOK
ABOUT THIS BOOK

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

TABLE OF CONTENTS
part I|2 pages
I Introduction and Overview
chapter 1|26 pages
Overview of Recent Developments for Interval-Censored Data
View abstract
chapter 2|14 pages
A Review of Various Models for Interval-Censored Data
View abstract
part II|2 pages
II Methodology
chapter 3|46 pages
Current Status Data in the Twenty-First Century
View abstract
chapter 4|22 pages
Regression Analysis for Current Status Data
View abstract
chapter 5|36 pages
Statistical Analysis of Dependent Current Status Data
View abstract
chapter 6|18 pages
Bayesian Semiparametric Regression Analysis of Interval- Censored Data with Monotone Splines
View abstract
chapter 7|30 pages
Bayesian Inference of Interval-Censored Survival Data
View abstract
chapter 8|36 pages
Targeted Minimum Loss–Based Estimation of a Causal Effect Using Interval-Censored Time-to-Event Data
View abstract
chapter 9|36 pages
Consistent Variance Estimation in Interval-Censored Data
View abstract
part III|2 pages
III Applications and Related Software
chapter 10|40 pages
Bias Assessment in Progression-Free Survival Analysis
View abstract
chapter 11|18 pages
Bias and Its Remedy in Interval-Censored Time-to-Event Applications
View abstract
chapter 12|16 pages
Adaptive Decision Making Based on Interval-Censored of Stroke
View abstract
chapter 13|32 pages
Practical Issues on Using Weighted Logrank Tests
View abstract
chapter 14|21 pages
glrt – New R Package for Analyzing Interval-Censored Sur- vival Data
View abstract

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

TABLE OF CONTENTS
part I|2 pages
I Introduction and Overview
chapter 1|26 pages
Overview of Recent Developments for Interval-Censored Data
View abstract
chapter 2|14 pages
A Review of Various Models for Interval-Censored Data
View abstract
part II|2 pages
II Methodology
chapter 3|46 pages
Current Status Data in the Twenty-First Century
View abstract
chapter 4|22 pages
Regression Analysis for Current Status Data
View abstract
chapter 5|36 pages
Statistical Analysis of Dependent Current Status Data
View abstract
chapter 6|18 pages
Bayesian Semiparametric Regression Analysis of Interval- Censored Data with Monotone Splines
View abstract
chapter 7|30 pages
Bayesian Inference of Interval-Censored Survival Data
View abstract
chapter 8|36 pages
Targeted Minimum Loss–Based Estimation of a Causal Effect Using Interval-Censored Time-to-Event Data
View abstract
chapter 9|36 pages
Consistent Variance Estimation in Interval-Censored Data
View abstract
part III|2 pages
III Applications and Related Software
chapter 10|40 pages
Bias Assessment in Progression-Free Survival Analysis
View abstract
chapter 11|18 pages
Bias and Its Remedy in Interval-Censored Time-to-Event Applications
View abstract
chapter 12|16 pages
Adaptive Decision Making Based on Interval-Censored of Stroke
View abstract
chapter 13|32 pages
Practical Issues on Using Weighted Logrank Tests
View abstract
chapter 14|21 pages
glrt – New R Package for Analyzing Interval-Censored Sur- vival Data
View abstract
Taylor & Francis Group
Policies
  • Privacy Policy
  • Terms & Conditions
  • Cookie Policy
Journals
  • Taylor & Francis Online
  • CogentOA
Corporate
  • Taylor & Francis
    Group
  • Taylor & Francis Group
Help & Contact
  • Students/Researchers
  • Librarians/Institutions

Connect with us

Registered in England & Wales No. 3099067
5 Howick Place | London | SW1P 1WG © 2018 Informa UK Limited