BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

136 related articles for article (PubMed ID: 38754869)

  • 41. An overview of confounding. Part 1: the concept and how to address it.
    Howards PP
    Acta Obstet Gynecol Scand; 2018 Apr; 97(4):394-399. PubMed ID: 29341103
    [TBL] [Abstract][Full Text] [Related]  

  • 42. Bias formulas for sensitivity analysis of unmeasured confounding for general outcomes, treatments, and confounders.
    Vanderweele TJ; Arah OA
    Epidemiology; 2011 Jan; 22(1):42-52. PubMed ID: 21052008
    [TBL] [Abstract][Full Text] [Related]  

  • 43. When measurement errors correlate with truth: surprising effects of nondifferential misclassification.
    Wacholder S
    Epidemiology; 1995 Mar; 6(2):157-61. PubMed ID: 7742402
    [TBL] [Abstract][Full Text] [Related]  

  • 44. Assessing causal treatment effect estimation when using large observational datasets.
    John ER; Abrams KR; Brightling CE; Sheehan NA
    BMC Med Res Methodol; 2019 Nov; 19(1):207. PubMed ID: 31726969
    [TBL] [Abstract][Full Text] [Related]  

  • 45. Bias in pharmacoepidemiologic studies using secondary health care databases: a scoping review.
    Prada-Ramallal G; Takkouche B; Figueiras A
    BMC Med Res Methodol; 2019 Mar; 19(1):53. PubMed ID: 30871502
    [TBL] [Abstract][Full Text] [Related]  

  • 46. Measurement error is often neglected in medical literature: a systematic review.
    Brakenhoff TB; Mitroiu M; Keogh RH; Moons KGM; Groenwold RHH; van Smeden M
    J Clin Epidemiol; 2018 Jun; 98():89-97. PubMed ID: 29522827
    [TBL] [Abstract][Full Text] [Related]  

  • 47. Bespoke Instruments: A new tool for addressing unmeasured confounders.
    Richardson DB; Tchetgen Tchetgen EJ
    Am J Epidemiol; 2022 Mar; 191(5):939-947. PubMed ID: 34907434
    [TBL] [Abstract][Full Text] [Related]  

  • 48. Overview of the epidemiology methods and applications: strengths and limitations of observational study designs.
    Colditz GA
    Crit Rev Food Sci Nutr; 2010; 50 Suppl 1(s1):10-2. PubMed ID: 21132580
    [TBL] [Abstract][Full Text] [Related]  

  • 49. 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]  

  • 50. Are We Missing Something Pertinent? A Bias Analysis of Unmeasured Confounding in the Firearm-Suicide Literature.
    Miller M; Swanson SA; Azrael D
    Epidemiol Rev; 2016; 38(1):62-9. PubMed ID: 26769723
    [TBL] [Abstract][Full Text] [Related]  

  • 51. 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]  

  • 52. Quantitative Bias Analysis for a Misclassified Confounder: A Comparison Between Marginal Structural Models and Conditional Models for Point Treatments.
    Nab L; Groenwold RHH; van Smeden M; Keogh RH
    Epidemiology; 2020 Nov; 31(6):796-805. PubMed ID: 32826524
    [TBL] [Abstract][Full Text] [Related]  

  • 53. Validity evaluation of indirect adjustment method for multiple unmeasured confounders: A simulation and empirical study.
    Byun G; Kim H; Kim SY; Kim SS; Oh H; Lee JT
    Environ Res; 2022 Mar; 204(Pt A):111992. PubMed ID: 34487697
    [TBL] [Abstract][Full Text] [Related]  

  • 54. Response to letter to the editor from Dr Rahman Shiri: The challenging topic of suicide across occupational groups.
    Niedhammer I; Milner A; Witt K; Klingelschmidt J; Khireddine-Medouni I; Alexopoulos EC; Toivanen S; Chastang JF; LaMontagne AD
    Scand J Work Environ Health; 2018 Jan; 44(1):108-110. PubMed ID: 29218357
    [TBL] [Abstract][Full Text] [Related]  

  • 55. 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]  

  • 56. A comparison of confounder selection and adjustment methods for estimating causal effects using large healthcare databases.
    Benasseur I; Talbot D; Durand M; Holbrook A; Matteau A; Potter BJ; Renoux C; Schnitzer ME; Tarride JÉ; Guertin JR
    Pharmacoepidemiol Drug Saf; 2022 Apr; 31(4):424-433. PubMed ID: 34953160
    [TBL] [Abstract][Full Text] [Related]  

  • 57. 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]  

  • 58. Regularized Regression Versus the High-Dimensional Propensity Score for Confounding Adjustment in Secondary Database Analyses.
    Franklin JM; Eddings W; Glynn RJ; Schneeweiss S
    Am J Epidemiol; 2015 Oct; 182(7):651-9. PubMed ID: 26233956
    [TBL] [Abstract][Full Text] [Related]  

  • 59. Effects of short-term exposure to air pollution on hospital admissions of young children for acute lower respiratory infections in Ho Chi Minh City, Vietnam.
    ; Le TG; Ngo L; Mehta S; Do VD; Thach TQ; Vu XD; Nguyen DT; Cohen A
    Res Rep Health Eff Inst; 2012 Jun; (169):5-72; discussion 73-83. PubMed ID: 22849236
    [TBL] [Abstract][Full Text] [Related]  

  • 60. Assessment and statistical modeling of the relationship between remotely sensed aerosol optical depth and PM2.5 in the eastern United States.
    Paciorek CJ; Liu Y;
    Res Rep Health Eff Inst; 2012 May; (167):5-83; discussion 85-91. PubMed ID: 22838153
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 7.