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 *

132 related articles for article (PubMed ID: 32687216)

  • 1. Analysis of noisy survival data with graphical proportional hazards measurement error models.
    Chen LP; Yi GY
    Biometrics; 2021 Sep; 77(3):956-969. PubMed ID: 32687216
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Application of random survival forests in understanding the determinants of under-five child mortality in Uganda in the presence of covariates that satisfy the proportional and non-proportional hazards assumption.
    Nasejje JB; Mwambi H
    BMC Res Notes; 2017 Sep; 10(1):459. PubMed ID: 28882171
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Accelerated failure time models with covariates subject to measurement error.
    He W; Yi GY; Xiong J
    Stat Med; 2007 Nov; 26(26):4817-32. PubMed ID: 17436310
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Analysis of error-prone survival data under additive hazards models: measurement error effects and adjustments.
    Yan Y; Yi GY
    Lifetime Data Anal; 2016 Jul; 22(3):321-42. PubMed ID: 26328545
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Semiparametric methods for survival data with measurement error under additive hazards cure rate models.
    Barui S; Yi GY
    Lifetime Data Anal; 2020 Jul; 26(3):421-450. PubMed ID: 31432384
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Simulation Extrapolation Method for Cox Regression Model with a Mixture of Berkson and Classical Errors in the Covariates using Calibration Data.
    Tapsoba JD; Chao EC; Wang CY
    Int J Biostat; 2019 Apr; 15(2):. PubMed ID: 30954972
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Bias analysis and the simulation-extrapolation method for survival data with covariate measurement error under parametric proportional odds models.
    Yi GY; He W
    Biom J; 2012 May; 54(3):343-60. PubMed ID: 22685001
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Cox regression with dependent error in covariates.
    Huang Y; Wang CY
    Biometrics; 2018 Mar; 74(1):118-126. PubMed ID: 28682458
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Data generation for the Cox proportional hazards model with time-dependent covariates: a method for medical researchers.
    Hendry DJ
    Stat Med; 2014 Feb; 33(3):436-54. PubMed ID: 24014094
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Flexible parametric approach to classical measurement error variance estimation without auxiliary data.
    Bertrand A; Van Keilegom I; Legrand C
    Biometrics; 2019 Mar; 75(1):297-307. PubMed ID: 30076713
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Correcting for Measurement Error in Time-Varying Covariates in Marginal Structural Models.
    Kyle RP; Moodie EE; Klein MB; Abrahamowicz M
    Am J Epidemiol; 2016 Aug; 184(3):249-58. PubMed ID: 27416840
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A smoothed corrected score approach for proportional hazards model with misclassified discretized covariates induced by error-contaminated continuous time-dependent exposure.
    Song X; Chao EC; Wang CY
    Biometrics; 2023 Mar; 79(1):437-448. PubMed ID: 34694632
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A semiparametric copula method for Cox models with covariate measurement error.
    Kim S; Li Y; Spiegelman D
    Lifetime Data Anal; 2016 Jan; 22(1):1-16. PubMed ID: 25504515
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Analysis of time-to-event data using a flexible mixture model under a constraint of proportional hazards.
    Liu GF; Liao JJZ
    J Biopharm Stat; 2020 Sep; 30(5):783-796. PubMed ID: 32589509
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Trend-constrained corrected score for proportional hazards model with covariate measurement error.
    Zhu M; Huang Y
    Contemp Clin Trials Commun; 2015 Oct; 1():5-16. PubMed ID: 29736434
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Evaluating survival model performance: a graphical approach.
    Mandel M; Galai N; Simchen E
    Stat Med; 2005 Jun; 24(12):1933-45. PubMed ID: 15806618
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Analysis of survival data with cure fraction and variable selection: A pseudo-observations approach.
    Su CL; Chiou SH; Lin FC; Platt RW
    Stat Methods Med Res; 2022 Nov; 31(11):2037-2053. PubMed ID: 35754373
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Generalized network structured models with mixed responses subject to measurement error and misclassification.
    Zhang Q; Yi GY
    Biometrics; 2023 Jun; 79(2):1073-1088. PubMed ID: 35032335
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Simulation-selection-extrapolation: Estimation in high-dimensional errors-in-variables models.
    Nghiem L; Potgieter C
    Biometrics; 2019 Dec; 75(4):1133-1144. PubMed ID: 31260084
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Testing the proportional hazards assumption in cox regression and dealing with possible non-proportionality in total joint arthroplasty research: methodological perspectives and review.
    Kuitunen I; Ponkilainen VT; Uimonen MM; Eskelinen A; Reito A
    BMC Musculoskelet Disord; 2021 May; 22(1):489. PubMed ID: 34049528
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.