國立高雄大學圖資館 |

登入

回首頁

Emerging topics in modeling interval-censored survival data

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Emerging topics in modeling interval-censored survival dataedited by Jianguo Sun, Ding-Geng Chen.
其他作者:	Sun, Jianguo.
出版者:	Cham :Springer International Publishing :2022.
面頁冊數:	xv, 313 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Censored observations (Statistics)
電子資源:	https://doi.org/10.1007/978-3-031-12366-5
ISBN:	9783031123665$q(electronic bk.)

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. - Cham :Springer International Publishing :2022. - xv, 313 p. :ill., digital ;24 cm. - 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$q(electronic bk.)

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

684029
Censored observations (Statistics)

LC Class. No.: QA276.6

Dewey Class. No.: 519.5

Emerging topics in modeling interval-censored survival data
LDR:02275nmm a2200325 a 4500 001 633531
003 DE-He213
005 20221129014521.0
006 m d
007 cr nn 008maaau
008 230511s2022 sz s 0 eng d
020 $a 9783031123665$q(electronic bk.)
020 $a 9783031123658$q(paper)
024 7 $a 10.1007/978-3-031-12366-5 $2 doi
035 $a 978-3-031-12366-5
040 $a GP $c GP
041 0 $a eng
050 4 $a QA276.6
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
072 7 $a PBT $2 thema
082 0 4 $a 519.5 $2 23
090 $a QA276.6 $b .E53 2022
245 0 0 $a Emerging topics in modeling interval-censored survival data $h [electronic resource] / $c edited by Jianguo Sun, Ding-Geng Chen.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a xv, 313 p. : $b ill., digital ; $c 24 cm.
490 1 $a ICSA book series in statistics, $x 2199-0999
520 $a 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.
650 0 $a Censored observations (Statistics) $3 684029
650 0 $a Statistics $x Methodology. $3 224891
700 1 $a Sun, Jianguo. $3 278588
700 1 $a Chen, Ding-Geng. $3 487343
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a ICSA book series in statistics. $3 725077
856 4 0 $u https://doi.org/10.1007/978-3-031-12366-5
950 $a Mathematics and Statistics (SpringerNature-11649)