153 related articles for article (PubMed ID: 11252614)
1. Factor analytic models of clustered multivariate data with informative censoring.
Dunson DB; Perreault SD
Biometrics; 2001 Mar; 57(1):302-8. PubMed ID: 11252614
[TBL] [Abstract][Full Text] [Related]
2. A frailty model for informative censoring.
Huang X; Wolfe RA
Biometrics; 2002 Sep; 58(3):510-20. PubMed ID: 12229985
[TBL] [Abstract][Full Text] [Related]
3. Bayesian models for multivariate current status data with informative censoring.
Dunson DB; Dinse GE
Biometrics; 2002 Mar; 58(1):79-88. PubMed ID: 11890330
[TBL] [Abstract][Full Text] [Related]
4. A Bayesian approach for joint modeling of cluster size and subunit-specific outcomes.
Dunson DB; Chen Z; Harry J
Biometrics; 2003 Sep; 59(3):521-30. PubMed ID: 14601753
[TBL] [Abstract][Full Text] [Related]
5. Joint analysis of longitudinal data with informative right censoring.
Liu M; Ying Z
Biometrics; 2007 Jun; 63(2):363-71. PubMed ID: 17425632
[TBL] [Abstract][Full Text] [Related]
6. Estimation efficiency and tests of covariate effects with clustered binary data.
Neuhaus JM
Biometrics; 1993 Dec; 49(4):989-96. PubMed ID: 8117909
[TBL] [Abstract][Full Text] [Related]
7. Generalized linear latent variable models for repeated measures of spatially correlated multivariate data.
Zhu J; Eickhoff JC; Yan P
Biometrics; 2005 Sep; 61(3):674-83. PubMed ID: 16135018
[TBL] [Abstract][Full Text] [Related]
8. Hidden Markov latent variable models with multivariate longitudinal data.
Song X; Xia Y; Zhu H
Biometrics; 2017 Mar; 73(1):313-323. PubMed ID: 27148857
[TBL] [Abstract][Full Text] [Related]
9. Normal frailty probit model for clustered interval-censored failure time data.
Wu H; Wang L
Biom J; 2019 Jul; 61(4):827-840. PubMed ID: 30838687
[TBL] [Abstract][Full Text] [Related]
10. Exact two-sample inference with missing data.
Cheung YK
Biometrics; 2005 Jun; 61(2):524-31. PubMed ID: 16011700
[TBL] [Abstract][Full Text] [Related]
11. Modelling multivariate outcomes in hierarchical data, with application to cluster randomised trials.
Turner RM; Omar RZ; Thompson SG
Biom J; 2006 Jun; 48(3):333-45. PubMed ID: 16845899
[TBL] [Abstract][Full Text] [Related]
12. A class of latent Markov models for capture-recapture data allowing for time, heterogeneity, and behavior effects.
Bartolucci F; Pennoni F
Biometrics; 2007 Jun; 63(2):568-78. PubMed ID: 17688509
[TBL] [Abstract][Full Text] [Related]
13. Maximum likelihood analysis of a general latent variable model with hierarchically mixed data.
Lee SY; Song XY
Biometrics; 2004 Sep; 60(3):624-36. PubMed ID: 15339284
[TBL] [Abstract][Full Text] [Related]
14. A latent autoregressive model for longitudinal binary data subject to informative missingness.
Albert PS; Follmann DA; Wang SA; Suh EB
Biometrics; 2002 Sep; 58(3):631-42. PubMed ID: 12229998
[TBL] [Abstract][Full Text] [Related]
15. Multilevel latent class models with dirichlet mixing distribution.
Di CZ; Bandeen-Roche K
Biometrics; 2011 Mar; 67(1):86-96. PubMed ID: 20560936
[TBL] [Abstract][Full Text] [Related]
16. Bayesian latent variable models for hierarchical clustered count outcomes with repeated measures in microbiome studies.
Xu L; Paterson AD; Xu W
Genet Epidemiol; 2017 Apr; 41(3):221-232. PubMed ID: 28111783
[TBL] [Abstract][Full Text] [Related]
17. Bayesian adaptive regression splines for hierarchical data.
Bigelow JL; Dunson DB
Biometrics; 2007 Sep; 63(3):724-32. PubMed ID: 17403106
[TBL] [Abstract][Full Text] [Related]
18. Parametric latent class joint model for a longitudinal biomarker and recurrent events.
Han J; Slate EH; Peña EA
Stat Med; 2007 Dec; 26(29):5285-302. PubMed ID: 17542002
[TBL] [Abstract][Full Text] [Related]
19. Fitting the log-F accelerated failure time model with incomplete covariate data.
Cho M; Schenker N
Biometrics; 1999 Sep; 55(3):826-33. PubMed ID: 11315013
[TBL] [Abstract][Full Text] [Related]
20. Modeling survival data with informative cluster size.
Williamson JM; Kim HY; Manatunga A; Addiss DG
Stat Med; 2008 Feb; 27(4):543-55. PubMed ID: 17640035
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]