Interval-censored time-to-event data : methods and applications / [edited by] Ding-Geng Chen, Jianguo Sun, Karl E. Peace.

Format:

Book

Contributor:

Chen, Ding-Geng.

Sun, Jianguo, 1961-

Peace, Karl E., 1941-

Series:

Chapman & Hall/CRC biostatistics series ; 52.

Chapman & Hall/CRC biostatistics series ; 52

Language:

English

Subjects (All):

Failure time data analysis.

Survival analysis (Biometry).

Clinical trials--Statistical methods.

Clinical trials.

Physical Description:

1 online resource (426 p.)

Edition:

1st edition

Place of Publication:

Boca Raton : Chapman and Hall/CRC, 2012.

Language Note:

English

System Details:

text file

Summary:

Preface The aim of this book is to present in a single volume an overview and latest developments in time-to-event interval-censored methods along with application of such methods. The book is divided into three parts. Part I provides an introduction and overview of time-to-event methods for interval-censored data. Methodology is presented in Part II. Applications and related software appear in Part III. Part I consists of two chapters. In Chapter 1, Sun and Li present an overview of recent developments, with attention to nonparametric estimation and comparison of survival functions, regression analysis, analysis of multivariate clustered- and analysis of competing risks interval-censored data. In Chapter 2, Yu and Hsu provide a review of models for interval-censored (IC) data, including: independent interval censorship models, the full likelihood model, various models for C1, C2, and MIC data as well as multivariate IC models. Part II consists of seven chapters (3-9). Chapters 3, 4 and 5 deal with interval-censored methods for current status data. In Chapter 3, Banerjee presents: likelihood based inference, more general forms of interval censoring, competing risks, smoothed estimators, inference on a grid, outcome misclassi- cation, and semiparametric models. In Chapter 4, Zhang presents regression analyses using the proportional hazards model, the proportional odds model, and a linear transformation model, as well as considering bivariate current status data with the proportional odds model. In Chapter 5, Kim, Kim, Nam and Kim develop statistical analysis methods for dependent current status data and utilize the R Package CSD to analyze such data-- Provided by publisher.

Contents:

Front Cover; Dedication; Contents; List of Figures; List of Tables; Preface; List of Contributors; I. Introduction and Overview; 1. Overview of Recent Developments for Interval-Censored Data; 2. A Review of Various Models for Interval-Censored Data; II. Methodology; 3. Current Status Data in the Twenty-First Century; 4. Regression Analysis for Current Status Data; 5. Statistical Analysis of Dependent Current Status Data; 6. Bayesian Semiparametric Regression Analysis of Interval- Censored Data with Monotone Splines; 7. Bayesian Inference of Interval-Censored Survival Data

8. Targeted Minimum Loss-Based Estimation of a Causal Effect Using Interval-Censored Time-to-Event Data9. Consistent Variance Estimation in Interval-Censored Data; III. Applications and Related Software; 10. Bias Assessment in Progression-Free Survival Analysis; 11. Bias and Its Remedy in Interval-Censored Time-to-Event Applications; 12. Adaptive Decision Making Based on Interval-Censored Data in a Clinical Trial to Optimize Rapid Treatment of Stroke; 13. Practical Issues on Using Weighted Logrank Tests; 14. glrt - New R Package for Analyzing Interval-Censored Survival Data

Notes:

A Chapman & Hall book.

Includes bibliographical references and index.

Description based on publisher supplied metadata and other sources.

ISBN:

9781040061008

1040061001

9780429096334

042909633X

9781466504288

1466504285

OCLC:

798535863