Emerging Topics In Modeling Interval-Censored Survival Data (Icsa Book Series In Statistics)

This book primarily aims to discuss emerging topics in statistical methods and to booster research, education, and training to advance statistical modeling on interval-censored survival data. Commonly collected from public health and biomedical research, among other sources, interval-censored survival data can easily be mistaken for typical right-censored survival data, which can result in erroneous statistical inference due to the complexity of this type of data. The book invites a group of internationally leading researchers to systematically discuss and explore the historical development of the associated methods and their computational implementations, as well as emerging topics related to interval-censored data. It covers a variety of topics, including univariate interval-censored data, multivariate interval-censored data, clustered interval-censored data, competing risk interval-censored data, data with interval-censored covariates, interval-censored data from electric medical records, and misclassified interval-censored data. Researchers, students, and practitioners can directly make use of the state-of-the-art methods covered in the book to tackle their problems in research, education, training and consultation.

• | Author: Jianguo Sun, Ding-Geng Chen
• | Publisher: Springer
• | Publication Date: Nov 30, 2022
• | Number of Pages: 328 pages
• | Language: English
• | Binding: Hardcover
• | ISBN-10: 3031123654
• | ISBN-13: 9783031123658