BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

351 related articles for article (PubMed ID: 16135036)

  • 1. Missing covariates in longitudinal data with informative dropouts: bias analysis and inference.
    Roy J; Lin X
    Biometrics; 2005 Sep; 61(3):837-46. PubMed ID: 16135036
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Analysis of change in the presence of informative censoring: application to a longitudinal clinical trial of progressive renal disease.
    Schluchter MD; Greene T; Beck GJ
    Stat Med; 2001 Apr; 20(7):989-1007. PubMed ID: 11276031
    [TBL] [Abstract][Full Text] [Related]  

  • 3. HIV viral dynamic models with dropouts and missing covariates.
    Wu L
    Stat Med; 2007 Jul; 26(17):3342-57. PubMed ID: 17221835
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Simple adjustments for randomized trials with nonrandomly missing or censored outcomes arising from informative covariates.
    Baker SG; Fitzmaurice GM; Freedman LS; Kramer BS
    Biostatistics; 2006 Jan; 7(1):29-40. PubMed ID: 15923407
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A bias correction in testing treatment efficacy under informative dropout in clinical trials.
    Kong F; Chen YF; Jin K
    J Biopharm Stat; 2009 Nov; 19(6):980-1000. PubMed ID: 20183460
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A comparison of two methods for the estimation of precision with incomplete longitudinal data, jointly modelled with a time-to-event outcome.
    Touloumi G; Babiker AG; Kenward MG; Pocock SJ; Darbyshire JH
    Stat Med; 2003 Oct; 22(20):3161-75. PubMed ID: 14518021
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A local sensitivity analysis approach to longitudinal non-Gaussian data with non-ignorable dropout.
    Xie H
    Stat Med; 2008 Jul; 27(16):3155-77. PubMed ID: 17948917
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A residuals-based transition model for longitudinal analysis with estimation in the presence of missing data.
    Koru-Sengul T; Stoffer DS; Day NL
    Stat Med; 2007 Jul; 26(17):3330-41. PubMed ID: 17124699
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Pseudo-likelihood methods for longitudinal binary data with non-ignorable missing responses and covariates.
    Parzen M; Lipsitz SR; Fitzmaurice GM; Ibrahim JG; Troxel A
    Stat Med; 2006 Aug; 25(16):2784-96. PubMed ID: 16345018
    [TBL] [Abstract][Full Text] [Related]  

  • 10. An alternative parameterization of the general linear mixture model for longitudinal data with non-ignorable drop-outs.
    Fitzmaurice GM; Laird NM; Shneyer L
    Stat Med; 2001 Apr; 20(7):1009-21. PubMed ID: 11276032
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Simultaneous inference for longitudinal data with detection limits and covariates measured with errors, with application to AIDS studies.
    Wu L
    Stat Med; 2004 Jun; 23(11):1715-31. PubMed ID: 15160404
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Structural inference in transition measurement error models for longitudinal data.
    Pan W; Lin X; Zeng D
    Biometrics; 2006 Jun; 62(2):402-12. PubMed ID: 16918904
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Joint modeling of longitudinal data and informative dropout time in the presence of multiple changepoints.
    Ghosh P; Ghosh K; Tiwari RC
    Stat Med; 2011 Mar; 30(6):611-26. PubMed ID: 21337357
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A hybrid model for nonignorable dropout in longitudinal binary responses.
    Wilkins KJ; Fitzmaurice GM
    Biometrics; 2006 Mar; 62(1):168-76. PubMed ID: 16542243
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Mixed effects logistic regression models for longitudinal binary response data with informative drop-out.
    Ten Have TR; Kunselman AR; Pulkstenis EP; Landis JR
    Biometrics; 1998 Mar; 54(1):367-83. PubMed ID: 9544529
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A copula model for repeated measurements with non-ignorable non-monotone missing outcome.
    Shen C; Weissfeld L
    Stat Med; 2006 Jul; 25(14):2427-40. PubMed ID: 16143999
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Bayesian analysis for generalized linear models with nonignorably missing covariates.
    Huang L; Chen MH; Ibrahim JG
    Biometrics; 2005 Sep; 61(3):767-80. PubMed ID: 16135028
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Joint inference for nonlinear mixed-effects models and time to event at the presence of missing data.
    Wu L; Hu XJ; Wu H
    Biostatistics; 2008 Apr; 9(2):308-20. PubMed ID: 17728318
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Marginalized transition models for longitudinal binary data with ignorable and non-ignorable drop-out.
    Kurland BF; Heagerty PJ
    Stat Med; 2004 Sep; 23(17):2673-95. PubMed ID: 15316952
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Semiparametric regression analysis of longitudinal data with informative drop-outs.
    Lin DY; Ying Z
    Biostatistics; 2003 Jul; 4(3):385-98. PubMed ID: 12925506
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 18.