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)

  • 21. Analysis of linear transformation models with covariate measurement error and interval censoring.
    Mandal S; Wang S; Sinha S
    Stat Med; 2019 Oct; 38(23):4642-4655. PubMed ID: 31347177
    [TBL] [Abstract][Full Text] [Related]  

  • 22. A general class of semiparametric transformation frailty models for nonproportional hazards survival data.
    Choi S; Huang X
    Biometrics; 2012 Dec; 68(4):1126-35. PubMed ID: 23005582
    [TBL] [Abstract][Full Text] [Related]  

  • 23. A comparison of the conditional inference survival forest model to random survival forests based on a simulation study as well as on two applications with time-to-event data.
    Nasejje JB; Mwambi H; Dheda K; Lesosky M
    BMC Med Res Methodol; 2017 Jul; 17(1):115. PubMed ID: 28754093
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Covariate dimension reduction for survival data via the Gaussian process latent variable model.
    Barrett JE; Coolen AC
    Stat Med; 2016 Apr; 35(8):1340-53. PubMed ID: 26526057
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Variable Selection and Inference Procedures for Marginal Analysis of Longitudinal Data with Missing Observations and Covariate Measurement Error.
    Yi GY; Tan X; Li R
    Can J Stat; 2015 Dec; 43(4):498-518. PubMed ID: 26877582
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Model diagnostics for the proportional hazards model with length-biased data.
    Lee CH; Ning J; Shen Y
    Lifetime Data Anal; 2019 Jan; 25(1):79-96. PubMed ID: 29450809
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Generating survival times to simulate Cox proportional hazards models.
    Bender R; Augustin T; Blettner M
    Stat Med; 2005 Jun; 24(11):1713-23. PubMed ID: 15724232
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Efficient semiparametric estimation of short-term and long-term hazard ratios with right-censored data.
    Diao G; Zeng D; Yang S
    Biometrics; 2013 Dec; 69(4):840-9. PubMed ID: 24328712
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Locally Efficient Semiparametric Estimators for Proportional Hazards Models with Measurement Error.
    Xu Y; Li Y; Song X
    Scand Stat Theory Appl; 2016 Jun; 43(2):558-572. PubMed ID: 27453626
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Inference for a family of survival models encompassing the proportional hazards and proportional odds models.
    Zucker DM; Yang S
    Stat Med; 2006 Mar; 25(6):995-1014. PubMed ID: 16220492
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Simulating survival data with predefined censoring rates for proportional hazards models.
    Wan F
    Stat Med; 2017 Feb; 36(5):838-854. PubMed ID: 27873333
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Survival analysis with error-prone time-varying covariates: a risk set calibration approach.
    Liao X; Zucker DM; Li Y; Spiegelman D
    Biometrics; 2011 Mar; 67(1):50-8. PubMed ID: 20486928
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Novel head and neck cancer survival analysis approach: random survival forests versus Cox proportional hazards regression.
    Datema FR; Moya A; Krause P; Bäck T; Willmes L; Langeveld T; Baatenburg de Jong RJ; Blom HM
    Head Neck; 2012 Jan; 34(1):50-8. PubMed ID: 21322080
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Feature screening with large-scale and high-dimensional survival data.
    Yi GY; He W; Carroll RJ
    Biometrics; 2022 Sep; 78(3):894-907. PubMed ID: 33881782
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Estimating the parameters in the Cox model when covariate variables are measured with error.
    Hu P; Tsiatis AA; Davidian M
    Biometrics; 1998 Dec; 54(4):1407-19. PubMed ID: 9883541
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Cox regression model under dependent truncation.
    Rennert L; Xie SX
    Biometrics; 2022 Jun; 78(2):460-473. PubMed ID: 33687064
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Dealing with the proportional hazards assumption when using the proportional hazards model with a single independent variable.
    Shibata A; Hamajima N; Tamakoshi A; Suzuki S; Sasaki R; Aoki K
    Jpn J Clin Oncol; 1989 Sep; 19(3):195-201. PubMed ID: 2810819
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Survival outcome prediction in cervical cancer: Cox models vs deep-learning model.
    Matsuo K; Purushotham S; Jiang B; Mandelbaum RS; Takiuchi T; Liu Y; Roman LD
    Am J Obstet Gynecol; 2019 Apr; 220(4):381.e1-381.e14. PubMed ID: 30582927
    [TBL] [Abstract][Full Text] [Related]  

  • 39. The single-index/Cox mixture cure model.
    Amico M; Van Keilegom I; Legrand C
    Biometrics; 2019 Jun; 75(2):452-462. PubMed ID: 30430553
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Graphing survival curve estimates for time-dependent covariates.
    Schultz LR; Peterson EL; Breslau N
    Int J Methods Psychiatr Res; 2002; 11(2):68-74. PubMed ID: 12459796
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 7.