149 related articles for article (PubMed ID: 23613620)
1. A semiparametric random effects model for multivariate competing risks data.
Scheike TH; Sun Y; Zhang MJ; Jensen TK
Biometrika; 2010 Mar; 97(1):133-145. PubMed ID: 23613620
[TBL] [Abstract][Full Text] [Related]
2. On cross-odds ratio for multivariate competing risks data.
Scheike TH; Sun Y
Biostatistics; 2012 Sep; 13(4):680-94. PubMed ID: 22696688
[TBL] [Abstract][Full Text] [Related]
3. Analysis of Generalized Semiparametric Regression Models for Cumulative Incidence Functions with Missing Covariates.
Lee U; Sun Y; Scheike TH; Gilbert PB
Comput Stat Data Anal; 2018 Jun; 122():59-79. PubMed ID: 29892140
[TBL] [Abstract][Full Text] [Related]
4. Semiparametric copula method for semi-competing risks data subject to interval censoring and left truncation: Application to disability in elderly.
Sun T; Li Y; Xiao Z; Ding Y; Wang X
Stat Methods Med Res; 2023 Apr; 32(4):656-670. PubMed ID: 36735020
[TBL] [Abstract][Full Text] [Related]
5. Association measures for clustered competing risks.
Su CL; Lakhal-Chaieb L
Stat Med; 2020 Feb; 39(4):409-423. PubMed ID: 31799731
[TBL] [Abstract][Full Text] [Related]
6. Estimating twin concordance for bivariate competing risks twin data.
Scheike TH; Holst KK; Hjelmborg JB
Stat Med; 2014 Mar; 33(7):1193-204. PubMed ID: 24132877
[TBL] [Abstract][Full Text] [Related]
7. Marginal semiparametric transformation models for clustered multivariate competing risks data.
He Y; Kim S; Mao L; Ahn KW
Stat Med; 2022 Nov; 41(26):5349-5364. PubMed ID: 36117139
[TBL] [Abstract][Full Text] [Related]
8. Bayesian bivariate survival analysis using the power variance function copula.
Romeo JS; Meyer R; Gallardo DI
Lifetime Data Anal; 2018 Apr; 24(2):355-383. PubMed ID: 28536818
[TBL] [Abstract][Full Text] [Related]
9. Semiparametric copula-based regression modeling of semi-competing risks data.
Zhu H; Lan Y; Ning J; Shen Y
Commun Stat Theory Methods; 2022; 51(22):7830-7845. PubMed ID: 36353187
[TBL] [Abstract][Full Text] [Related]
10. Semiparametric marginal regression for clustered competing risks data with missing cause of failure.
Zhou W; Bakoyannis G; Zhang Y; Yiannoutsos CT
Biostatistics; 2023 Jul; 24(3):795-810. PubMed ID: 35411923
[TBL] [Abstract][Full Text] [Related]
11. Semiparametric regression and risk prediction with competing risks data under missing cause of failure.
Bakoyannis G; Zhang Y; Yiannoutsos CT
Lifetime Data Anal; 2020 Oct; 26(4):659-684. PubMed ID: 31982977
[TBL] [Abstract][Full Text] [Related]
12. Efficient Estimation of Semiparametric Transformation Models for the Cumulative Incidence of Competing Risks.
Mao L; Lin DY
J R Stat Soc Series B Stat Methodol; 2017 Mar; 79(2):573-587. PubMed ID: 28239261
[TBL] [Abstract][Full Text] [Related]
13. Maximum likelihood estimation of semiparametric mixture component models for competing risks data.
Choi S; Huang X
Biometrics; 2014 Sep; 70(3):588-98. PubMed ID: 24734912
[TBL] [Abstract][Full Text] [Related]
14. Semiparametric mixture cure model analysis with competing risks data: Application to vascular access thrombosis data.
Chen CM; Shen PS; Lin CC; Wu CC
Stat Med; 2020 Nov; 39(27):4086-4099. PubMed ID: 32790100
[TBL] [Abstract][Full Text] [Related]
15. Modeling the cumulative incidence function of multivariate competing risks data allowing for within-cluster dependence of risk and timing.
Cederkvist L; Holst KK; Andersen KK; Scheike TH
Biostatistics; 2019 Apr; 20(2):199-217. PubMed ID: 29309528
[TBL] [Abstract][Full Text] [Related]
16. Estimation of conditional cumulative incidence functions under generalized semiparametric regression models with missing covariates, with application to analysis of biomarker correlates in vaccine trials.
Sun Y; Heng F; Lee U; Gilbert PB
Can J Stat; 2023 Mar; 51(1):235-257. PubMed ID: 36937899
[TBL] [Abstract][Full Text] [Related]
17. Association analysis of successive events data in the presence of competing risks.
Chen X; Cheng Y; Frank E; Kupfer DJ
Stat Methods Med Res; 2018 Jun; 27(6):1661-1682. PubMed ID: 27647813
[TBL] [Abstract][Full Text] [Related]
18. Improved confidence intervals for a difference of two cause-specific cumulative incidence functions estimated in the presence of competing risks and random censoring.
Scosyrev E
Biom J; 2020 Oct; 62(6):1394-1407. PubMed ID: 32227361
[TBL] [Abstract][Full Text] [Related]
19. A two-stage estimation in the Clayton-Oakes model with marginal linear transformation models for multivariate failure time data.
Chen CM; Yu CY
Lifetime Data Anal; 2012 Jan; 18(1):94-115. PubMed ID: 21983914
[TBL] [Abstract][Full Text] [Related]
20. Semiparametric regression analysis of interval-censored competing risks data.
Mao L; Lin DY; Zeng D
Biometrics; 2017 Sep; 73(3):857-865. PubMed ID: 28211951
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]