Dewey Class |
519.5 |
Title |
Emerging Topics in Modeling Interval-Censored Survival Data ( EBook/) / edited by Jianguo Sun, Ding-Geng Chen. |
Added Personal Name |
Sun, Jianguo |
Chen, Ding-Geng |
Other name(s) |
SpringerLink (Online service) |
Edition statement |
1st ed. 2022. |
Publication |
Cham : : Springer International Publishing : : Imprint: Springer, , 2022. |
Physical Details |
XV, 313 p. 1 illus. : online resource. |
Series |
ICSA Book Series in Statistics 2199-0999 |
ISBN |
9783031123665 |
Summary Note |
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.: |
Mode of acces to digital resource |
Digital reproduction.- |
Cham : |
Springer International Publishing, |
2022. - |
Mode of access: World Wide Web. System requirements: Internet Explorer 6.0 (or higher) or Firefox 2.0 (or higher). Available as searchable text in PDF format. |
System details note |
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users). |
Internet Site |
https://doi.org/10.1007/978-3-031-12366-5 |
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