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 *

153 related articles for article (PubMed ID: 29577376)

  • 1. Dynamic prediction of cumulative incidence functions by direct binomial regression.
    Grand MK; de Witte TJM; Putter H
    Biom J; 2018 Jul; 60(4):734-747. PubMed ID: 29577376
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Dynamic pseudo-observations: a robust approach to dynamic prediction in competing risks.
    Nicolaie MA; van Houwelingen JC; de Witte TM; Putter H
    Biometrics; 2013 Dec; 69(4):1043-52. PubMed ID: 23865523
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Comparison of joint modeling and landmarking for dynamic prediction under an illness-death model.
    Suresh K; Taylor JMG; Spratt DE; Daignault S; Tsodikov A
    Biom J; 2017 Nov; 59(6):1277-1300. PubMed ID: 28508545
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Analysis of Generalized Semiparametric Regression Models for Cumulative Incidence Functions with Missing Covariates.
    Lee U; Sun Y; Scheike TH; Gilbert PB
    Comput Stat Data Anal; 2018 Jun; 122():59-79. PubMed ID: 29892140
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. Quantifying and comparing dynamic predictive accuracy of joint models for longitudinal marker and time-to-event in presence of censoring and competing risks.
    Blanche P; Proust-Lima C; Loubère L; Berr C; Dartigues JF; Jacqmin-Gadda H
    Biometrics; 2015 Mar; 71(1):102-113. PubMed ID: 25311240
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Regression modeling of competing risks data based on pseudovalues of the cumulative incidence function.
    Klein JP; Andersen PK
    Biometrics; 2005 Mar; 61(1):223-9. PubMed ID: 15737097
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Evaluating predictors of competing risk outcomes when censoring depends on time-dependent covariates, with application to safety and efficacy of HIV treatment.
    Lok JJ; Hughes MD
    Stat Med; 2016 Jun; 35(13):2183-94. PubMed ID: 26763556
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Partly conditional survival models for longitudinal data.
    Zheng Y; Heagerty PJ
    Biometrics; 2005 Jun; 61(2):379-91. PubMed ID: 16011684
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Measures of single arm outcome in meta-analyses of rare events in the presence of competing risks.
    Andreano A; Rebora P; Valsecchi MG
    Biom J; 2015 Jul; 57(4):649-60. PubMed ID: 25656709
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Covariate adjustment of cumulative incidence functions for competing risks data using inverse probability of treatment weighting.
    Neumann A; Billionnet C
    Comput Methods Programs Biomed; 2016 Jun; 129():63-70. PubMed ID: 27084321
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Stagewise pseudo-value regression for time-varying effects on the cumulative incidence.
    Zöller D; Schmidtmann I; Weinmann A; Gerds TA; Binder H
    Stat Med; 2016 Mar; 35(7):1144-58. PubMed ID: 26510388
    [TBL] [Abstract][Full Text] [Related]  

  • 13. The importance of censoring in competing risks analysis of the subdistribution hazard.
    Donoghoe MW; Gebski V
    BMC Med Res Methodol; 2017 Apr; 17(1):52. PubMed ID: 28376736
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Association analysis of successive events data in the presence of competing risks.
    Chen X; Cheng Y; Frank E; Kupfer DJ
    Stat Methods Med Res; 2018 Jun; 27(6):1661-1682. PubMed ID: 27647813
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Dynamic clinical prediction models for discrete time-to-event data with competing risks-A case study on the OUTCOMEREA database.
    Heyard R; Timsit JF; Essaied W; Held L;
    Biom J; 2019 May; 61(3):514-534. PubMed ID: 30221403
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Penalized estimation for competing risks regression with applications to high-dimensional covariates.
    Ambrogi F; Scheike TH
    Biostatistics; 2016 Oct; 17(4):708-21. PubMed ID: 27118123
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A Proportional Hazards Regression Model for the Sub-distribution with Covariates Adjusted Censoring Weight for Competing Risks Data.
    He P; Eriksson F; Scheike TH; Zhang MJ
    Scand Stat Theory Appl; 2016 Mar; 43(1):103-122. PubMed ID: 27034534
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Constrained parametric model for simultaneous inference of two cumulative incidence functions.
    Shi H; Cheng Y; Jeong JH
    Biom J; 2013 Jan; 55(1):82-96. PubMed ID: 23090878
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Nonparametric inference for the cumulative incidence function of a competing risk, with an emphasis on confidence bands in the presence of left-truncation.
    Di Termini S; Hieke S; Schumacher M; Beyersmann J
    Biom J; 2012 Jul; 54(4):568-78. PubMed ID: 22610530
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Flexible regression model selection for survival probabilities: with application to AIDS.
    DiRienzo AG
    Biometrics; 2009 Dec; 65(4):1194-202. PubMed ID: 19173693
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.