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 *

110 related articles for article (PubMed ID: 36513267)

  • 21. More robust estimation of average treatment effects using kernel optimal matching in an observational study of spine surgical interventions.
    Kallus N; Pennicooke B; Santacatterina M
    Stat Med; 2021 May; 40(10):2305-2320. PubMed ID: 33665870
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Instrumental variables and inverse probability weighting for causal inference from longitudinal observational studies.
    Hogan JW; Lancaster T
    Stat Methods Med Res; 2004 Feb; 13(1):17-48. PubMed ID: 14746439
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Causal inference in longitudinal studies with history-restricted marginal structural models.
    Neugebauer R; van der Laan MJ; Joffe MM; Tager IB
    Electron J Stat; 2007 Jan; 1():119-154. PubMed ID: 23087778
    [TBL] [Abstract][Full Text] [Related]  

  • 24. A simulation-based marginal method for longitudinal data with dropout and mismeasured covariates.
    Yi GY
    Biostatistics; 2008 Jul; 9(3):501-12. PubMed ID: 18199691
    [TBL] [Abstract][Full Text] [Related]  

  • 25. A Bayesian nonparametric approach to marginal structural models for point treatments and a continuous or survival outcome.
    Roy J; Lum KJ; Daniels MJ
    Biostatistics; 2017 Jan; 18(1):32-47. PubMed ID: 27345532
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Interval-cohort designs and bias in the estimation of per-protocol effects: a simulation study.
    Young JG; Vatsa R; Murray EJ; Hernán MA
    Trials; 2019 Sep; 20(1):552. PubMed ID: 31488202
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Joint modeling of concurrent binary outcomes in a longitudinal observational study using inverse probability of treatment weighting for treatment effect estimation.
    Agogo GO; Murphy TE; McAvay GJ; Allore HG
    Ann Epidemiol; 2019 Jul; 35():53-58. PubMed ID: 31085069
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Variance reduction in randomised trials by inverse probability weighting using the propensity score.
    Williamson EJ; Forbes A; White IR
    Stat Med; 2014 Feb; 33(5):721-37. PubMed ID: 24114884
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Doubly Robust and Efficient Estimation of Marginal Structural Models for the Hazard Function.
    Zheng W; Petersen M; van der Laan MJ
    Int J Biostat; 2016 May; 12(1):233-52. PubMed ID: 27227723
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Structural Nested Cumulative Failure Time Models to Estimate the Effects of Interventions.
    Picciotto S; Hernán MA; Page JH; Young JG; Robins JM
    J Am Stat Assoc; 2012; 107(499):. PubMed ID: 24347749
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Survival analysis using inverse probability of treatment weighted methods based on the generalized propensity score.
    Sugihara M
    Pharm Stat; 2010; 9(1):21-34. PubMed ID: 19199275
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Inverse probability weighting with error-prone covariates.
    McCaffrey DF; Lockwood JR; Setodji CM
    Biometrika; 2013; 100(3):671-680. PubMed ID: 24795484
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Comparing g-computation, propensity score-based weighting, and targeted maximum likelihood estimation for analyzing externally controlled trials with both measured and unmeasured confounders: a simulation study.
    Ren J; Cislo P; Cappelleri JC; Hlavacek P; DiBonaventura M
    BMC Med Res Methodol; 2023 Jan; 23(1):18. PubMed ID: 36647031
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Data-adaptive longitudinal model selection in causal inference with collaborative targeted minimum loss-based estimation.
    Schnitzer ME; Sango J; Ferreira Guerra S; van der Laan MJ
    Biometrics; 2020 Mar; 76(1):145-157. PubMed ID: 31397506
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Causal inference in survival analysis using longitudinal observational data: Sequential trials and marginal structural models.
    Keogh RH; Gran JM; Seaman SR; Davies G; Vansteelandt S
    Stat Med; 2023 Jun; 42(13):2191-2225. PubMed ID: 37086186
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Targeted maximum likelihood based causal inference: Part I.
    van der Laan MJ
    Int J Biostat; 2010; 6(2):Article 2. PubMed ID: 21969992
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Causal effect estimation strategies in a longitudinal study with complex time-varying confounders: A tutorial.
    Mertens BJ; Datta S; Brand R; Peul W
    Stat Methods Med Res; 2017 Feb; 26(1):337-355. PubMed ID: 25147227
    [TBL] [Abstract][Full Text] [Related]  

  • 38. On Bayesian estimation of marginal structural models.
    Saarela O; Stephens DA; Moodie EE; Klein MB
    Biometrics; 2015 Jun; 71(2):279-88. PubMed ID: 25677103
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Adjusted Kaplan-Meier estimator and log-rank test with inverse probability of treatment weighting for survival data.
    Xie J; Liu C
    Stat Med; 2005 Oct; 24(20):3089-110. PubMed ID: 16189810
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Double robust estimator of average causal treatment effect for censored medical cost data.
    Wang X; Beste LA; Maier MM; Zhou XH
    Stat Med; 2016 Aug; 35(18):3101-16. PubMed ID: 26818601
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 6.