BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

449 related articles for article (PubMed ID: 25687168)

  • 1. Limitations of individual causal models, causal graphs, and ignorability assumptions, as illustrated by random confounding and design unfaithfulness.
    Greenland S; Mansournia MA
    Eur J Epidemiol; 2015 Oct; 30(10):1101-10. PubMed ID: 25687168
    [TBL] [Abstract][Full Text] [Related]  

  • 2. [A structural classification of strategies for confounding control in research design].
    He YN; Liu LL; Cai QY; Zhao NQ; Zheng YJ
    Zhonghua Liu Xing Bing Xue Za Zhi; 2018 Jul; 39(7):999-1002. PubMed ID: 30060319
    [TBL] [Abstract][Full Text] [Related]  

  • 3. On the causal structure of information bias and confounding bias in randomized trials.
    Shahar E; Shahar DJ
    J Eval Clin Pract; 2009 Dec; 15(6):1214-6. PubMed ID: 20367730
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A counterfactual approach to bias and effect modification in terms of response types.
    Suzuki E; Mitsuhashi T; Tsuda T; Yamamoto E
    BMC Med Res Methodol; 2013 Jul; 13():101. PubMed ID: 23902658
    [TBL] [Abstract][Full Text] [Related]  

  • 5. [Time-dependent confounding in the estimation of treatment effects in randomised trials with multimodal therapies--an illustration of the problem of time-dependent confounding by causal graphs].
    Zietemann VD; Schuster T; Duell TH
    Gesundheitswesen; 2015 Jan; 77(1):62-6. PubMed ID: 24203687
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Causal Diagrams: Pitfalls and Tips.
    Suzuki E; Shinozaki T; Yamamoto E
    J Epidemiol; 2020 Apr; 30(4):153-162. PubMed ID: 32009103
    [TBL] [Abstract][Full Text] [Related]  

  • 7. [Causal Inference in Medicine Part II. Directed acyclic graphs--a useful method for confounder selection, categorization of potential biases, and hypothesis specification].
    Suzuki E; Komatsu H; Yorifuji T; Yamamoto E; Doi H; Tsuda T
    Nihon Eiseigaku Zasshi; 2009 Sep; 64(4):796-805. PubMed ID: 19797848
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Bounds on potential risks and causal risk differences under assumptions about confounding parameters.
    Chiba Y; Sato T; Greenland S
    Stat Med; 2007 Dec; 26(28):5125-35. PubMed ID: 17525935
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Mendelian randomization as an instrumental variable approach to causal inference.
    Didelez V; Sheehan N
    Stat Methods Med Res; 2007 Aug; 16(4):309-30. PubMed ID: 17715159
    [TBL] [Abstract][Full Text] [Related]  

  • 10. What random assignment does and does not do.
    Krause MS; Howard KI
    J Clin Psychol; 2003 Jul; 59(7):751-66. PubMed ID: 12808582
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Introduction to causal diagrams for confounder selection.
    Williamson EJ; Aitken Z; Lawrie J; Dharmage SC; Burgess JA; Forbes AB
    Respirology; 2014 Apr; 19(3):303-11. PubMed ID: 24447391
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Graphical Models for Quasi-experimental Designs.
    Steiner PM; Kim Y; Hall CE; Su D
    Sociol Methods Res; 2017 Mar; 46(2):155-188. PubMed ID: 30174355
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Causal Methods for Observational Research: A Primer.
    Almasi-Hashiani A; Nedjat S; Mansournia MA
    Arch Iran Med; 2018 Apr; 21(4):164-169. PubMed ID: 29693407
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Errors in causal inference: an organizational schema for systematic error and random error.
    Suzuki E; Tsuda T; Mitsuhashi T; Mansournia MA; Yamamoto E
    Ann Epidemiol; 2016 Nov; 26(11):788-793.e1. PubMed ID: 27771142
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Instruments for causal inference: an epidemiologist's dream?
    Hernán MA; Robins JM
    Epidemiology; 2006 Jul; 17(4):360-72. PubMed ID: 16755261
    [TBL] [Abstract][Full Text] [Related]  

  • 16. [Causal analysis approaches in epidemiology].
    Dumas O; Siroux V; Le Moual N; Varraso R
    Rev Epidemiol Sante Publique; 2014 Feb; 62(1):53-63. PubMed ID: 24388738
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Model Averaging for Improving Inference from Causal Diagrams.
    Hamra GB; Kaufman JS; Vahratian A
    Int J Environ Res Public Health; 2015 Aug; 12(8):9391-407. PubMed ID: 26270672
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Dependence of confounding on the target population: a modification of causal graphs to account for co-action.
    Flanders WD; Johnson CY; Howards PP; Greenland S
    Ann Epidemiol; 2011 Sep; 21(9):698-705. PubMed ID: 21737305
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Graphical presentation of confounding in directed acyclic graphs.
    Suttorp MM; Siegerink B; Jager KJ; Zoccali C; Dekker FW
    Nephrol Dial Transplant; 2015 Sep; 30(9):1418-23. PubMed ID: 25324358
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Causal graphical views of fixed effects and random effects models.
    Kim Y; Steiner PM
    Br J Math Stat Psychol; 2021 May; 74(2):165-183. PubMed ID: 33063334
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 23.