172 related articles for article (PubMed ID: 21983914)
1. 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]
2. Estimation and testing for clustered interval-censored bivariate survival data with application using the semi-parametric version of the Clayton-Oakes model.
Rosner B; Bay C; Glynn RJ; Ying GS; Maguire MG; Lee MT
Lifetime Data Anal; 2023 Oct; 29(4):854-887. PubMed ID: 36670299
[TBL] [Abstract][Full Text] [Related]
3. Multivariate continuation ratio models: connections and caveats.
Heagerty PJ; Zeger SL
Biometrics; 2000 Sep; 56(3):719-32. PubMed ID: 10985208
[TBL] [Abstract][Full Text] [Related]
4. Additive transformation models for clustered failure time data.
Zeng D; Cai J
Lifetime Data Anal; 2010 Jul; 16(3):333-52. PubMed ID: 20012358
[TBL] [Abstract][Full Text] [Related]
5. A two-stage estimator of the dependence parameter for the Clayton-Oakes model.
Glidden DV
Lifetime Data Anal; 2000 Jun; 6(2):141-56. PubMed ID: 10851839
[TBL] [Abstract][Full Text] [Related]
6. Likelihood approaches for proportional likelihood ratio model with right-censored data.
Zhu H
Stat Med; 2014 Jun; 33(14):2467-79. PubMed ID: 24500821
[TBL] [Abstract][Full Text] [Related]
7. On the Plackett distribution with bivariate censored data.
Ghosh D
Int J Biostat; 2008; 4(1):Article 7. PubMed ID: 22462114
[TBL] [Abstract][Full Text] [Related]
8. Flexible maximum likelihood methods for bivariate proportional hazards models.
He W; Lawless JF
Biometrics; 2003 Dec; 59(4):837-48. PubMed ID: 14969462
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. Checking the linear transformation model for clustered failure time observations.
Hattori S
Lifetime Data Anal; 2008 Sep; 14(3):253-66. PubMed ID: 18240021
[TBL] [Abstract][Full Text] [Related]
11. Likelihood ratio procedures and tests of fit in parametric and semiparametric copula models with censored data.
Yilmaz YE; Lawless JF
Lifetime Data Anal; 2011 Jul; 17(3):386-408. PubMed ID: 21279545
[TBL] [Abstract][Full Text] [Related]
12. Marginally specified logistic-normal models for longitudinal binary data.
Heagerty PJ
Biometrics; 1999 Sep; 55(3):688-98. PubMed ID: 11314994
[TBL] [Abstract][Full Text] [Related]
13. Modeling multivariate discrete failure time data.
Shih JH
Biometrics; 1998 Sep; 54(3):1115-28. PubMed ID: 9750256
[TBL] [Abstract][Full Text] [Related]
14. A joint modeling approach for multivariate survival data with random length.
Liu S; Manatunga AK; Peng L; Marcus M
Biometrics; 2017 Jun; 73(2):666-677. PubMed ID: 27704528
[TBL] [Abstract][Full Text] [Related]
15. A readily available improvement over method of moments for intra-cluster correlation estimation in the context of cluster randomized trials and fitting a GEE-type marginal model for binary outcomes.
Westgate PM
Clin Trials; 2019 Feb; 16(1):41-51. PubMed ID: 30295512
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Semiparametric Maximum Likelihood Estimation in Normal Transformation Models for Bivariate Survival Data.
Li Y; Prentice RL; Lin X
Biometrika; 2008 Dec; 95(4):947-960. PubMed ID: 19079778
[TBL] [Abstract][Full Text] [Related]
18. Estimation of time-dependent association for bivariate failure times in the presence of a competing risk.
Ning J; Bandeen-Roche K
Biometrics; 2014 Mar; 70(1):10-20. PubMed ID: 24350628
[TBL] [Abstract][Full Text] [Related]
19. Analysis of clustered failure time data with cure fraction using copula.
Su CL; Lin FC
Stat Med; 2019 Sep; 38(21):3961-3973. PubMed ID: 31162705
[TBL] [Abstract][Full Text] [Related]
20. A likelihood reformulation method in non-normal random effects models.
Liu L; Yu Z
Stat Med; 2008 Jul; 27(16):3105-24. PubMed ID: 18038445
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
