BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

163 related articles for article (PubMed ID: 38412300)

  • 1. Using instrumental variables to address unmeasured confounding in causal mediation analysis.
    Rudolph KE; Williams N; Díaz I
    Biometrics; 2024 Jan; 80(1):. PubMed ID: 38412300
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Identification and robust estimation of swapped direct and indirect effects: Mediation analysis with unmeasured mediator-outcome confounding and intermediate confounding.
    Tai AS; Lin SH
    Stat Med; 2022 Sep; 41(21):4143-4158. PubMed ID: 35716042
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Practical causal mediation analysis: extending nonparametric estimators to accommodate multiple mediators and multiple intermediate confounders.
    Rudolph KE; Williams NT; Diaz I
    Biostatistics; 2024 Apr; ():. PubMed ID: 38576206
    [TBL] [Abstract][Full Text] [Related]  

  • 4. The impact of unmeasured within- and between-cluster confounding on the bias of effect estimatorsof a continuous exposure.
    Li Y; Lee Y; Port FK; Robinson BM
    Stat Methods Med Res; 2020 Aug; 29(8):2119-2139. PubMed ID: 31694489
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Causal mediation analysis with sure outcomes of random events model.
    Li W; Geng Z; Zhou XH
    Stat Med; 2021 Jul; 40(17):3975-3989. PubMed ID: 33902164
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A principled approach to mediation analysis in perinatal epidemiology.
    Ananth CV; Brandt JS
    Am J Obstet Gynecol; 2022 Jan; 226(1):24-32.e6. PubMed ID: 34991898
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Bayesian sensitivity analysis for unmeasured confounding in causal mediation analysis.
    McCandless LC; Somers JM
    Stat Methods Med Res; 2019 Feb; 28(2):515-531. PubMed ID: 28882092
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Weighted estimators of the complier average causal effect on restricted mean survival time with observed instrument-outcome confounders.
    Dharmarajan SH; Li Y; Lehmann D; Schaubel DE
    Biom J; 2021 Apr; 63(4):712-724. PubMed ID: 33346382
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways.
    Burgess S; Daniel RM; Butterworth AS; Thompson SG;
    Int J Epidemiol; 2015 Apr; 44(2):484-95. PubMed ID: 25150977
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Adjusting for Baseline Measurements of the Mediators and Outcome as a First Step Toward Eliminating Confounding Biases in Mediation Analysis.
    Loh WW; Ren D
    Perspect Psychol Sci; 2023 Sep; 18(5):1254-1266. PubMed ID: 36749872
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Estimation of Natural Indirect Effects Robust to Unmeasured Confounding and Mediator Measurement Error.
    Fulcher IR; Shi X; Tchetgen Tchetgen EJ
    Epidemiology; 2019 Nov; 30(6):825-834. PubMed ID: 31478915
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Distribution-free mediation analysis for nonlinear models with confounding.
    Albert JM
    Epidemiology; 2012 Nov; 23(6):879-88. PubMed ID: 23007042
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Stein-like estimators for causal mediation analysis in randomized trials.
    Ginestet CE; Emsley R; Landau S
    Stat Methods Med Res; 2020 Apr; 29(4):1129-1148. PubMed ID: 31172884
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Mediation analysis with multiple mediators under unmeasured mediator-outcome confounding.
    Wickramarachchi DS; Lim LHM; Sun B
    Stat Med; 2023 Feb; 42(4):422-432. PubMed ID: 36502820
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Instrumental variable methods for causal inference.
    Baiocchi M; Cheng J; Small DS
    Stat Med; 2014 Jun; 33(13):2297-340. PubMed ID: 24599889
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Unifying instrumental variable and inverse probability weighting approaches for inference of causal treatment effect and unmeasured confounding in observational studies.
    Liu T; Hogan JW
    Stat Methods Med Res; 2021 Mar; 30(3):671-686. PubMed ID: 33213292
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Identification of natural direct effects when a confounder of the mediator is directly affected by exposure.
    Tchetgen Tchetgen EJ; Vanderweele TJ
    Epidemiology; 2014 Mar; 25(2):282-91. PubMed ID: 24487211
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Bayesian data fusion: Probabilistic sensitivity analysis for unmeasured confounding using informative priors based on secondary data.
    Comment L; Coull BA; Zigler C; Valeri L
    Biometrics; 2022 Jun; 78(2):730-741. PubMed ID: 33527348
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Assessing moderated mediation in linear models requires fewer confounding assumptions than assessing mediation.
    Loeys T; Talloen W; Goubert L; Moerkerke B; Vansteelandt S
    Br J Math Stat Psychol; 2016 Nov; 69(3):352-374. PubMed ID: 27711981
    [TBL] [Abstract][Full Text] [Related]  

  • 20. [Probe variables: a tool for identification of unmeasured confounders in an observational study].
    Hong X; Yin JC; Wang B
    Zhonghua Liu Xing Bing Xue Za Zhi; 2021 Apr; 42(4):735-739. PubMed ID: 34814460
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.