These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

115 related articles for article (PubMed ID: 28762523)

  • 1. Prediction accuracy and variable selection for penalized cause-specific hazards models.
    Saadati M; Beyersmann J; Kopp-Schneider A; Benner A
    Biom J; 2018 Mar; 60(2):288-306. PubMed ID: 28762523
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Variable selection in subdistribution hazard frailty models with competing risks data.
    Ha ID; Lee M; Oh S; Jeong JH; Sylvester R; Lee Y
    Stat Med; 2014 Nov; 33(26):4590-604. PubMed ID: 25042872
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Regularized Weighted Nonparametric Likelihood Approach for High-Dimension Sparse Subdistribution Hazards Model for Competing Risk Data.
    Tapak L; Kosorok MR; Sadeghifar M; Hamidi O; Afshar S; Doosti H
    Comput Math Methods Med; 2021; 2021():5169052. PubMed ID: 34589136
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Penalized variable selection in competing risks regression.
    Fu Z; Parikh CR; Zhou B
    Lifetime Data Anal; 2017 Jul; 23(3):353-376. PubMed ID: 27016934
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Penalized variable selection for cause-specific hazard frailty models with clustered competing-risks data.
    Rakhmawati TW; Ha ID; Lee H; Lee Y
    Stat Med; 2021 Dec; 40(29):6541-6557. PubMed ID: 34541690
    [TBL] [Abstract][Full Text] [Related]  

  • 6. High-dimensional variable selection and prediction under competing risks with application to SEER-Medicare linked data.
    Hou J; Paravati A; Hou J; Xu R; Murphy J
    Stat Med; 2018 Oct; 37(24):3486-3502. PubMed ID: 29845637
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Modelling two cause-specific hazards of competing risks in one cumulative proportional odds model?
    Ohneberg K; Schumacher M; Beyersmann J
    Stat Med; 2017 Nov; 36(27):4353-4363. PubMed ID: 28833435
    [TBL] [Abstract][Full Text] [Related]  

  • 8. High-dimensional feature selection in competing risks modeling: A stable approach using a split-and-merge ensemble algorithm.
    Sun H; Wang X
    Biom J; 2023 Feb; 65(2):e2100164. PubMed ID: 35934836
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Communicating and understanding statistical measures when quantifying the between-group difference in competing risks.
    Wu H; Zhang C; Hou Y; Chen Z
    Int J Epidemiol; 2023 Dec; 52(6):1975-1983. PubMed ID: 37738672
    [TBL] [Abstract][Full Text] [Related]  

  • 10. L1 penalized estimation in the Cox proportional hazards model.
    Goeman JJ
    Biom J; 2010 Feb; 52(1):70-84. PubMed ID: 19937997
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Patient death as a censoring event or competing risk event in models of nursing home placement.
    Szychowski JM; Roth DL; Clay OJ; Mittelman MS
    Stat Med; 2010 Feb; 29(3):371-81. PubMed ID: 20014354
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. Cause-specific cumulative incidence estimation and the fine and gray model under both left truncation and right censoring.
    Geskus RB
    Biometrics; 2011 Mar; 67(1):39-49. PubMed ID: 20377575
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Competing risks data analysis with high-dimensional covariates: an application in bladder cancer.
    Tapak L; Saidijam M; Sadeghifar M; Poorolajal J; Mahjub H
    Genomics Proteomics Bioinformatics; 2015 Jun; 13(3):169-76. PubMed ID: 25907251
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Fast Lasso-type safe screening for Fine-Gray competing risks model with ultrahigh dimensional covariates.
    Wang H; Shen Z; Tan Z; Zhang Z; Li G
    Stat Med; 2022 Oct; 41(24):4941-4960. PubMed ID: 35946065
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Boosting for high-dimensional time-to-event data with competing risks.
    Binder H; Allignol A; Schumacher M; Beyersmann J
    Bioinformatics; 2009 Apr; 25(7):890-6. PubMed ID: 19244389
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Coupled variable selection for regression modeling of complex treatment patterns in a clinical cancer registry.
    Schmidtmann I; Elsäßer A; Weinmann A; Binder H
    Stat Med; 2014 Dec; 33(30):5358-70. PubMed ID: 25345575
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Artificial neural network for the joint modelling of discrete cause-specific hazards.
    Biganzoli EM; Boracchi P; Ambrogi F; Marubini E
    Artif Intell Med; 2006 Jun; 37(2):119-30. PubMed ID: 16730963
    [TBL] [Abstract][Full Text] [Related]  

  • 19. High-dimensional Cox models: the choice of penalty as part of the model building process.
    Benner A; Zucknick M; Hielscher T; Ittrich C; Mansmann U
    Biom J; 2010 Feb; 52(1):50-69. PubMed ID: 20166132
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Time-dependent covariates in the proportional subdistribution hazards model for competing risks.
    Beyersmann J; Schumacher M
    Biostatistics; 2008 Oct; 9(4):765-76. PubMed ID: 18434297
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.