東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Survival analysis with correlated en...

Emura, Takeshi.

FindBook

Google Book

Amazon

博客來

Survival analysis with correlated endpoints = joint frailty-copula models /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Survival analysis with correlated endpoints/ by Takeshi Emura, Shigeyuki Matsui, Virginie Rondeau.
其他題名:	joint frailty-copula models /
作者:	Emura, Takeshi.
其他作者:	Matsui, Shigeyuki.
出版者:	Singapore :Springer Singapore : : 2019.,
面頁冊數:	xvii, 118 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
標題:	Survival analysis (Biometry) -
電子資源:	https://doi.org/10.1007/978-981-13-3516-7
ISBN:	9789811335167

Survival analysis with correlated endpoints = joint frailty-copula models /
Emura, Takeshi.

Survival analysis with correlated endpointsjoint frailty-copula models /[electronic resource] :by Takeshi Emura, Shigeyuki Matsui, Virginie Rondeau. - Singapore :Springer Singapore :2019. - xvii, 118 p. :ill. (some col.), digital ;24 cm. - JSS research series in statistics,2364-0057. - JSS research series in statistics..

This book introduces readers to advanced statistical methods for analyzing survival data involving correlated endpoints. In particular, it describes statistical methods for applying Cox regression to two correlated endpoints by accounting for dependence between the endpoints with the aid of copulas. The practical advantages of employing copula-based models in medical research are explained on the basis of case studies. In addition, the book focuses on clustered survival data, especially data arising from meta-analysis and multicenter analysis. Consequently, the statistical approaches presented here employ a frailty term for heterogeneity modeling. This brings the joint frailty-copula model, which incorporates a frailty term and a copula, into a statistical model. The book also discusses advanced techniques for dealing with high-dimensional gene expressions and developing personalized dynamic prediction tools under the joint frailty-copula model. To help readers apply the statistical methods to real-world data, the book provides case studies using the authors' original R software package (freely available in CRAN) The emphasis is on clinical survival data, involving time-to-tumor progression and overall survival, collected on cancer patients. Hence, the book offers an essential reference guide for medical statisticians and provides researchers with advanced, innovative statistical tools. The book also provides a concise introduction to basic multivariate survival models.

ISBN: 9789811335167

Standard No.: 10.1007/978-981-13-3516-7doiSubjects--Topical Terms:

648175
Survival analysis (Biometry)

LC Class. No.: QA276

Dewey Class. No.: 519.546

Survival analysis with correlated endpoints = joint frailty-copula models /
LDR:02596nmm a2200337 a 4500 001 2180661
003 DE-He213
005 20190325135146.0
006 m d
007 cr nn 008maaau
008 191122s2019 si s 0 eng d
020 $a 9789811335167 $q (electronic bk.)
020 $a 9789811335150 $q (paper)
024 7 $a 10.1007/978-981-13-3516-7 $2 doi
035 $a 978-981-13-3516-7
040 $a GP $c GP
041 0 $a eng
050 4 $a QA276
072 7 $a PBT $2 bicssc
072 7 $a MED090000 $2 bisacsh
072 7 $a PBT $2 thema
072 7 $a MBNS $2 thema
082 0 4 $a 519.546 $2 23
090 $a QA276 $b .E55 2019
100 1 $a Emura, Takeshi. $3 3309051
245 1 0 $a Survival analysis with correlated endpoints $h [electronic resource] : $b joint frailty-copula models / $c by Takeshi Emura, Shigeyuki Matsui, Virginie Rondeau.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2019.
300 $a xvii, 118 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a JSS research series in statistics, $x 2364-0057
520 $a This book introduces readers to advanced statistical methods for analyzing survival data involving correlated endpoints. In particular, it describes statistical methods for applying Cox regression to two correlated endpoints by accounting for dependence between the endpoints with the aid of copulas. The practical advantages of employing copula-based models in medical research are explained on the basis of case studies. In addition, the book focuses on clustered survival data, especially data arising from meta-analysis and multicenter analysis. Consequently, the statistical approaches presented here employ a frailty term for heterogeneity modeling. This brings the joint frailty-copula model, which incorporates a frailty term and a copula, into a statistical model. The book also discusses advanced techniques for dealing with high-dimensional gene expressions and developing personalized dynamic prediction tools under the joint frailty-copula model. To help readers apply the statistical methods to real-world data, the book provides case studies using the authors' original R software package (freely available in CRAN) The emphasis is on clinical survival data, involving time-to-tumor progression and overall survival, collected on cancer patients. Hence, the book offers an essential reference guide for medical statisticians and provides researchers with advanced, innovative statistical tools. The book also provides a concise introduction to basic multivariate survival models.
650 0 $a Survival analysis (Biometry) $3 648175
650 1 4 $a Statistics for Life Sciences, Medicine, Health Sciences. $3 891086
650 2 4 $a Statistics for Social Sciences, Humanities, Law. $3 3382004
650 2 4 $a Statistical Theory and Methods. $3 891074
650 2 4 $a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 1005896
700 1 $a Matsui, Shigeyuki. $3 3264802
700 1 $a Rondeau, Virginie. $3 3386948
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a JSS research series in statistics. $3 3386949
856 4 0 $u https://doi.org/10.1007/978-981-13-3516-7
950 $a Mathematics and Statistics (Springer-11649)