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Results: 1 to 20 of 137

Related Citations for PubMed (Select 22344869)

1.

Joint analysis of bivariate longitudinal ordinal outcomes and competing risks survival times with nonparametric distributions for random effects.

Li N, Elashoff RM, Li G, Tseng CH.

Stat Med. 2012 Jul 20;31(16):1707-21. doi: 10.1002/sim.4507. Epub 2012 Feb 17.

PMID:
22344869
2.

A joint model for longitudinal measurements and survival data in the presence of multiple failure types.

Elashoff RM, Li G, Li N.

Biometrics. 2008 Sep;64(3):762-71. Epub 2007 Dec 20.

3.

Joint modeling of longitudinal ordinal data and competing risks survival times and analysis of the NINDS rt-PA stroke trial.

Li N, Elashoff RM, Li G, Saver J.

Stat Med. 2010 Feb 28;29(5):546-57. doi: 10.1002/sim.3798.

4.

Robust joint modeling of longitudinal measurements and competing risks failure time data.

Li N, Elashoff RM, Li G.

Biom J. 2009 Feb;51(1):19-30. doi: 10.1002/bimj.200810491.

5.

Joint modeling of survival and longitudinal data: likelihood approach revisited.

Hsieh F, Tseng YK, Wang JL.

Biometrics. 2006 Dec;62(4):1037-43.

PMID:
17156277
6.
7.

Latent-variable models for longitudinal data with bivariate ordinal outcomes.

Todem D, Kim K, Lesaffre E.

Stat Med. 2007 Feb 28;26(5):1034-54.

PMID:
16832841
8.
9.

Joint analysis of longitudinal data with informative right censoring.

Liu M, Ying Z.

Biometrics. 2007 Jun;63(2):363-71. Epub 2007 Apr 9.

PMID:
17425632
10.

A semiparametric likelihood approach to joint modeling of longitudinal and time-to-event data.

Song X, Davidian M, Tsiatis AA.

Biometrics. 2002 Dec;58(4):742-53.

PMID:
12495128
11.

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. doi: 10.1007/s10985-011-9205-1. Epub 2011 Oct 9.

PMID:
21983914
12.

Approximate nonparametric corrected-score method for joint modeling of survival and longitudinal data measured with error.

de Dieu Tapsoba J, Lee SM, Wang CY.

Biom J. 2011 Jul;53(4):557-77. doi: 10.1002/bimj.201000180.

13.
14.

Semi-parametric modelling of the distribution of the baseline risk in meta-analysis.

Ghidey W, Lesaffre E, Stijnen T.

Stat Med. 2007 Dec 30;26(30):5434-44.

PMID:
17893888
15.

A general joint model for longitudinal measurements and competing risks survival data with heterogeneous random effects.

Huang X, Li G, Elashoff RM, Pan J.

Lifetime Data Anal. 2011 Jan;17(1):80-100. doi: 10.1007/s10985-010-9169-6. Epub 2010 Jun 12.

16.
17.

A Bayesian approach to joint analysis of longitudinal measurements and competing risks failure time data.

Hu W, Li G, Li N.

Stat Med. 2009 May 15;28(11):1601-19. doi: 10.1002/sim.3562.

18.

Latent variable models for multivariate longitudinal ordinal responses.

Cagnone S, Moustaki I, Vasdekis V.

Br J Math Stat Psychol. 2009 May;62(Pt 2):401-15. doi: 10.1348/000711008X320134. Epub 2008 Jul 11.

PMID:
18625083
19.

A joint model for survival and longitudinal data measured with error.

Wulfsohn MS, Tsiatis AA.

Biometrics. 1997 Mar;53(1):330-9.

PMID:
9147598
20.

A bivariate approach to meta-analysis.

Van Houwelingen HC, Zwinderman KH, Stijnen T.

Stat Med. 1993 Dec 30;12(24):2273-84.

PMID:
7907813
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