BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

184 related articles for article (PubMed ID: 18482060)

  • 1. Sensitivity analysis: distributional assumptions and confounding assumptions.
    Vanderweele TJ
    Biometrics; 2008 Jun; 64(2):645-9. PubMed ID: 18482060
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Assessing the sensitivity of regression results to unmeasured confounders in observational studies.
    Lin DY; Psaty BM; Kronmal RA
    Biometrics; 1998 Sep; 54(3):948-63. PubMed ID: 9750244
    [TBL] [Abstract][Full Text] [Related]  

  • 3. The sign of the unmeasured confounding bias under various standard populations.
    Chiba Y
    Biom J; 2009 Aug; 51(4):670-6. PubMed ID: 19650054
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Regression analysis of panel count data with dependent observation times.
    Sun J; Tong X; He X
    Biometrics; 2007 Dec; 63(4):1053-9. PubMed ID: 18078478
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A comparison of methods to estimate the survivor average causal effect in the presence of missing data: a simulation study.
    McGuinness MB; Kasza J; Karahalios A; Guymer RH; Finger RP; Simpson JA
    BMC Med Res Methodol; 2019 Dec; 19(1):223. PubMed ID: 31795945
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Assessing the impact of unmeasured confounding for binary outcomes using confounding functions.
    Kasza J; Wolfe R; Schuster T
    Int J Epidemiol; 2017 Aug; 46(4):1303-1311. PubMed ID: 28338913
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Sensitivity analyses for unmeasured confounding assuming a marginal structural model for repeated measures.
    Brumback BA; Hernán MA; Haneuse SJ; Robins JM
    Stat Med; 2004 Mar; 23(5):749-67. PubMed ID: 14981673
    [TBL] [Abstract][Full Text] [Related]  

  • 8. The case-time-control design: further assumptions and conditions.
    Suissa S
    Epidemiology; 1998 Jul; 9(4):441-5. PubMed ID: 9647910
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Bounds on controlled direct effects under monotonic assumptions about mediators and confounders.
    Chiba Y
    Biom J; 2010 Oct; 52(5):628-37. PubMed ID: 20886528
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Bias Formulas for Estimating Direct and Indirect Effects When Unmeasured Confounding Is Present.
    le Cessie S
    Epidemiology; 2016 Jan; 27(1):125-32. PubMed ID: 26426943
    [TBL] [Abstract][Full Text] [Related]  

  • 11. The sign of the bias of unmeasured confounding.
    VanderWeele TJ
    Biometrics; 2008 Sep; 64(3):702-706. PubMed ID: 18177462
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Estimation in semiparametric transition measurement error models for longitudinal data.
    Pan W; Zeng D; Lin X
    Biometrics; 2009 Sep; 65(3):728-36. PubMed ID: 19173696
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Extensions of the penalized spline of propensity prediction method of imputation.
    Zhang G; Little R
    Biometrics; 2009 Sep; 65(3):911-8. PubMed ID: 19053998
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Evaluating the impact of unmeasured confounding with internal validation data: an example cost evaluation in type 2 diabetes.
    Faries D; Peng X; Pawaskar M; Price K; Stamey JD; Seaman JW
    Value Health; 2013; 16(2):259-66. PubMed ID: 23538177
    [TBL] [Abstract][Full Text] [Related]  

  • 15. EVALUATING COSTS WITH UNMEASURED CONFOUNDING: A SENSITIVITY ANALYSIS FOR THE TREATMENT EFFECT.
    Handorf EA; Bekelman JE; Heitjan DF; Mitra N
    Ann Appl Stat; 2013; 7(4):2062-2080. PubMed ID: 24587844
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A More Efficient Causal Mediator Model Without the No-Unmeasured-Confounder Assumption.
    Brandt H
    Multivariate Behav Res; 2020; 55(4):531-552. PubMed ID: 31497999
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Two-stage instrumental variable methods for estimating the causal odds ratio: analysis of bias.
    Cai B; Small DS; Have TR
    Stat Med; 2011 Jul; 30(15):1809-24. PubMed ID: 21495062
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Sensitivity analysis for causal inference under unmeasured confounding and measurement error problems.
    Díaz I; van der Laan MJ
    Int J Biostat; 2013 Nov; 9(2):149-60. PubMed ID: 24246288
    [TBL] [Abstract][Full Text] [Related]  

  • 19. How unmeasured confounding in a competing risks setting can affect treatment effect estimates in observational studies.
    Barrowman MA; Peek N; Lambie M; Martin GP; Sperrin M
    BMC Med Res Methodol; 2019 Jul; 19(1):166. PubMed ID: 31366331
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A new criterion for confounder selection.
    VanderWeele TJ; Shpitser I
    Biometrics; 2011 Dec; 67(4):1406-13. PubMed ID: 21627630
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.