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Emerging Topics in Modeling Interval-Censored Survival Data

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Emerging Topics in Modeling Interval-Censored Survival Data/ edited by Jianguo Sun, Ding-Geng Chen.
其他作者:	Chen, Ding-Geng.
面頁冊數:	XV, 313 p. 1 illus.online resource. :
Contained By:	Springer Nature eBook
標題:	Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences. -
電子資源:	https://doi.org/10.1007/978-3-031-12366-5
ISBN:	9783031123665

Emerging Topics in Modeling Interval-Censored Survival Data
Emerging Topics in Modeling Interval-Censored Survival Data[electronic resource] /edited by Jianguo Sun, Ding-Geng Chen. - 1st ed. 2022. - XV, 313 p. 1 illus.online resource. - ICSA Book Series in Statistics,2199-0999. - 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.

ISBN: 9783031123665

Standard No.: 10.1007/978-3-031-12366-5doiSubjects--Topical Terms:

1366002
Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.

LC Class. No.: QA276-280

Dewey Class. No.: 519.5

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