BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

456 related articles for article (PubMed ID: 12652556)

  • 1. An EM-based semi-parametric mixture model approach to the regression analysis of competing-risks data.
    Ng SK; McLachlan GJ
    Stat Med; 2003 Apr; 22(7):1097-111. PubMed ID: 12652556
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Semi-parametric estimation in failure time mixture models.
    Taylor JM
    Biometrics; 1995 Sep; 51(3):899-907. PubMed ID: 7548707
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A new estimation method for the semiparametric accelerated failure time mixture cure model.
    Zhang J; Peng Y
    Stat Med; 2007 Jul; 26(16):3157-71. PubMed ID: 17094075
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Polynomial spline estimation and inference of proportional hazards regression models with flexible relative risk form.
    Huang JZ; Liu L
    Biometrics; 2006 Sep; 62(3):793-802. PubMed ID: 16984322
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Joint models for efficient estimation in proportional hazards regression models.
    Slasor P; Laird N
    Stat Med; 2003 Jul; 22(13):2137-48. PubMed ID: 12820279
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Applying Cox regression to competing risks.
    Lunn M; McNeil D
    Biometrics; 1995 Jun; 51(2):524-32. PubMed ID: 7662841
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Estimation method of the semiparametric mixture cure gamma frailty model.
    Peng Y; Zhang J
    Stat Med; 2008 Nov; 27(25):5177-94. PubMed ID: 18613271
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A SAS macro for parametric and semiparametric mixture cure models.
    Corbière F; Joly P
    Comput Methods Programs Biomed; 2007 Feb; 85(2):173-80. PubMed ID: 17157948
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Prediction of cumulative incidence function under the proportional hazards model.
    Cheng SC; Fine JP; Wei LJ
    Biometrics; 1998 Mar; 54(1):219-28. PubMed ID: 9544517
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Analyses of cumulative incidence functions via non-parametric multiple imputation.
    Ruan PK; Gray RJ
    Stat Med; 2008 Nov; 27(27):5709-24. PubMed ID: 18712779
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Fully parametric and semi-parametric regression models for common events with covariate measurement error in main study/validation study designs.
    Spiegelman D; Casella M
    Biometrics; 1997 Jun; 53(2):395-409. PubMed ID: 9192443
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Semi-parametric differential expression analysis via partial mixture estimation.
    Rossell D; Guerra R; Scott C
    Stat Appl Genet Mol Biol; 2008; 7(1):Article15. PubMed ID: 18454730
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Bayesian adjustment for covariate measurement errors: a flexible parametric approach.
    Hossain S; Gustafson P
    Stat Med; 2009 May; 28(11):1580-600. PubMed ID: 19226564
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A hierarchical model for binary data with dependence between the design and outcome success probabilities.
    Todem D; Williams KP
    Stat Med; 2009 Oct; 28(24):2967-88. PubMed ID: 19642075
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Direct likelihood inference and sensitivity analysis for competing risks regression with missing causes of failure.
    Moreno-Betancur M; Rey G; Latouche A
    Biometrics; 2015 Jun; 71(2):498-507. PubMed ID: 25761785
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A multiple imputation approach for clustered interval-censored survival data.
    Lam KF; Xu Y; Cheung TL
    Stat Med; 2010 Mar; 29(6):680-93. PubMed ID: 20069624
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Application of pattern-mixture models to outcomes that are potentially missing not at random using pseudo maximum likelihood estimation.
    Shen C; Weissfeld L
    Biostatistics; 2005 Apr; 6(2):333-47. PubMed ID: 15772110
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Non-parametric estimation for baseline hazards function and covariate effects with time-dependent covariates.
    Gao F; Manatunga AK; Chen S
    Stat Med; 2007 Feb; 26(4):857-68. PubMed ID: 16685705
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Semi-parametric regression models for cost-effectiveness analysis: improving the efficiency of estimation from censored data.
    Pullenayegum EM; Willan AR
    Stat Med; 2007 Jul; 26(17):3274-99. PubMed ID: 17309112
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Marginal estimation for multi-stage models: waiting time distributions and competing risks analyses.
    Satten GA; Datta S
    Stat Med; 2002 Jan; 21(1):3-19. PubMed ID: 11782047
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 23.