BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

246 related articles for article (PubMed ID: 30111382)

  • 1. Sources of confounding in life course epidemiology.
    Santos S; Zugna D; Pizzi C; Richiardi L
    J Dev Orig Health Dis; 2019 Jun; 10(3):299-305. PubMed ID: 30111382
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Mediation analysis in epidemiology: methods, interpretation and bias.
    Richiardi L; Bellocco R; Zugna D
    Int J Epidemiol; 2013 Oct; 42(5):1511-9. PubMed ID: 24019424
    [TBL] [Abstract][Full Text] [Related]  

  • 3. The impact of residual and unmeasured confounding in epidemiologic studies: a simulation study.
    Fewell Z; Davey Smith G; Sterne JA
    Am J Epidemiol; 2007 Sep; 166(6):646-55. PubMed ID: 17615092
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Relationship between mediation analysis and the structured life course approach.
    Howe LD; Smith AD; Macdonald-Wallis C; Anderson EL; Galobardes B; Lawlor DA; Ben-Shlomo Y; Hardy R; Cooper R; Tilling K; Fraser A
    Int J Epidemiol; 2016 Aug; 45(4):1280-1294. PubMed ID: 27681097
    [TBL] [Abstract][Full Text] [Related]  

  • 5. An overview of confounding. Part 2: how to identify it and special situations.
    Howards PP
    Acta Obstet Gynecol Scand; 2018 Apr; 97(4):400-406. PubMed ID: 29341101
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Epidemiologic studies: pitfalls in interpretation.
    Westhoff CL
    Dialogues Contracept; 1995; 4(5):5-6, 8. PubMed ID: 12288680
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. Bounding formulas for selection bias.
    Huang TH; Lee WC
    Am J Epidemiol; 2015 Nov; 182(10):868-72. PubMed ID: 26519426
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Use of Causal Diagrams to Inform the Design and Interpretation of Observational Studies: An Example from the Study of Heart and Renal Protection (SHARP).
    Staplin N; Herrington WG; Judge PK; Reith CA; Haynes R; Landray MJ; Baigent C; Emberson J
    Clin J Am Soc Nephrol; 2017 Mar; 12(3):546-552. PubMed ID: 27553952
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Bias in Clinical Research.
    Stuckless S; Parfrey PS
    Methods Mol Biol; 2021; 2249():17-34. PubMed ID: 33871836
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Applying the E Value to Assess the Robustness of Epidemiologic Fields of Inquiry to Unmeasured Confounding.
    Trinquart L; Erlinger AL; Petersen JM; Fox M; Galea S
    Am J Epidemiol; 2019 Jun; 188(6):1174-1180. PubMed ID: 30874728
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Good research practices for comparative effectiveness research: approaches to mitigate bias and confounding in the design of nonrandomized studies of treatment effects using secondary data sources: the International Society for Pharmacoeconomics and Outcomes Research Good Research Practices for Retrospective Database Analysis Task Force Report--Part II.
    Cox E; Martin BC; Van Staa T; Garbe E; Siebert U; Johnson ML
    Value Health; 2009; 12(8):1053-61. PubMed ID: 19744292
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A most stubborn bias: no adjustment method fully resolves confounding by indication in observational studies.
    Bosco JL; Silliman RA; Thwin SS; Geiger AM; Buist DS; Prout MN; Yood MU; Haque R; Wei F; Lash TL
    J Clin Epidemiol; 2010 Jan; 63(1):64-74. PubMed ID: 19457638
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Fixed effects analysis of repeated measures data.
    Gunasekara FI; Richardson K; Carter K; Blakely T
    Int J Epidemiol; 2014 Feb; 43(1):264-9. PubMed ID: 24366487
    [TBL] [Abstract][Full Text] [Related]  

  • 15. [Sensitivity analysis method for unmeasured confounding interference in observational study].
    Wang DH; You DF; Huang LL; Zhao Y
    Zhonghua Liu Xing Bing Xue Za Zhi; 2019 Nov; 40(11):1470-1475. PubMed ID: 31838823
    [No Abstract]   [Full Text] [Related]  

  • 16. General concepts in biostatistics and clinical epidemiology: observational studies with case-control design.
    Martínez D; Papuzinski C; Stojanova J; Arancibia M
    Medwave; 2019 Nov; 19(10):e7716. PubMed ID: 31821315
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Does exposure prediction bias health-effect estimation?: The relationship between confounding adjustment and exposure prediction.
    Cefalu M; Dominici F
    Epidemiology; 2014 Jul; 25(4):583-90. PubMed ID: 24815302
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Simpson's paradox and experimental research.
    Ameringer S; Serlin RC; Ward S
    Nurs Res; 2009; 58(2):123-7. PubMed ID: 19289933
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Confounding in health research.
    Greenland S; Morgenstern H
    Annu Rev Public Health; 2001; 22():189-212. PubMed ID: 11274518
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Distinguishing Selection Bias and Confounding Bias in Comparative Effectiveness Research.
    Haneuse S
    Med Care; 2016 Apr; 54(4):e23-9. PubMed ID: 24309675
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 13.