These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

439 related articles for article (PubMed ID: 24366487)

  • 1. 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]  

  • 2. Prior event rate ratio adjustment: numerical studies of a statistical method to address unrecognized confounding in observational studies.
    Yu M; Xie D; Wang X; Weiner MG; Tannen RL
    Pharmacoepidemiol Drug Saf; 2012 May; 21 Suppl 2():60-8. PubMed ID: 22552981
    [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. 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]  

  • 5. 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]  

  • 6. A sensitivity analysis using information about measured confounders yielded improved uncertainty assessments for unmeasured confounding.
    McCandless LC; Gustafson P; Levy AR
    J Clin Epidemiol; 2008 Mar; 61(3):247-55. PubMed ID: 18226747
    [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. 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]  

  • 9. Confounding of indirect effects: a sensitivity analysis exploring the range of bias due to a cause common to both the mediator and the outcome.
    Hafeman DM
    Am J Epidemiol; 2011 Sep; 174(6):710-7. PubMed ID: 21652602
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Statistical methods for epidemiologic studies of the health effects of air pollution.
    Navidi W; Thomas D; Langholz B; Stram D
    Res Rep Health Eff Inst; 1999 May; (86):1-50; discussion 51-6. PubMed ID: 10465799
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. Adjusting for bias and unmeasured confounding in Mendelian randomization studies with binary responses.
    Palmer TM; Thompson JR; Tobin MD; Sheehan NA; Burton PR
    Int J Epidemiol; 2008 Oct; 37(5):1161-8. PubMed ID: 18463132
    [TBL] [Abstract][Full Text] [Related]  

  • 13. On a preference-based instrumental variable approach in reducing unmeasured confounding-by-indication.
    Li Y; Lee Y; Wolfe RA; Morgenstern H; Zhang J; Port FK; Robinson BM
    Stat Med; 2015 Mar; 34(7):1150-68. PubMed ID: 25546152
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. Interpreting treatment-effect estimates with heterogeneity and choice: simulation model results.
    Brooks JM; Fang G
    Clin Ther; 2009 Apr; 31(4):902-19. PubMed ID: 19446162
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Bayesian modeling of cost-effectiveness studies with unmeasured confounding: a simulation study.
    Stamey JD; Beavers DP; Faries D; Price KL; Seaman JW
    Pharm Stat; 2014; 13(1):94-100. PubMed ID: 24446072
    [TBL] [Abstract][Full Text] [Related]  

  • 17. The missing cause approach to unmeasured confounding in pharmacoepidemiology.
    Abrahamowicz M; Bjerre LM; Beauchamp ME; LeLorier J; Burne R
    Stat Med; 2016 Mar; 35(7):1001-16. PubMed ID: 26932124
    [TBL] [Abstract][Full Text] [Related]  

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

  • 19. 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]  

  • 20. Hierarchical priors for bias parameters in Bayesian sensitivity analysis for unmeasured confounding.
    McCandless LC; Gustafson P; Levy AR; Richardson S
    Stat Med; 2012 Feb; 31(4):383-96. PubMed ID: 22253142
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 22.