Quantifying the impact of unmeasured confounding in observational studies with the E value

被引:8
|
作者
Gaster, Tobias [1 ]
Eggertsen, Christine Marie [1 ]
Stovring, Henrik [2 ,3 ]
Ehrenstein, Vera [4 ,5 ]
Petersen, Irene [4 ,5 ,6 ]
机构
[1] Aarhus Univ, Aarhus, Denmark
[2] Steno Diabet Ctr Aarhus, Aarhus, Denmark
[3] Univ Southern Denmark, Clin Pharmacol Pharm & Environm Med, Odense, Denmark
[4] Aarhus Univ, Dept Clin Epidemiol, DK-8000 Aarhus, Denmark
[5] Aarhus Univ Hosp, Aarhus, Denmark
[6] UCL, Dept Primary Care & Populat Hlth, London, England
来源
BMJ MEDICINE | 2023年 / 2卷 / 01期
关键词
Pregnancy complications; Epidemiology; Obstetrics; SEROTONIN REUPTAKE INHIBITORS; SENSITIVITY-ANALYSIS; MISCARRIAGE; PREGNANCY; RISK;
D O I
10.1136/bmjmed-2022-000366
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
The E value method deals with unmeasured confounding, a key source of bias in observational studies. The E value method is described and its use is shown in a worked example of a meta-analysis examining the association between the use of antidepressants in pregnancy and the risk of miscarriage.
引用
收藏
页数:5
相关论文
共 50 条
  • [31] Accounting for Confounding in Observational Studies
    D'Onofrio, Brian M.
    Sjolander, Arvid
    Lahey, Benjamin B.
    Lichtenstein, Paul
    Oberg, A. Sara
    ANNUAL REVIEW OF CLINICAL PSYCHOLOGY, VOL 16, 2020, 2020, 16 : 25 - 48
  • [32] Residual Confounding in Observational Studies
    Ho, Kwok Ming
    ANESTHESIOLOGY, 2009, 110 (02) : 430 - 430
  • [33] Quantifying the impact of survivor treatment bias in observational studies
    Austin, Peter C.
    Mamdani, Muhammad M.
    van Walraven, Carl
    Tu, Jack V.
    JOURNAL OF EVALUATION IN CLINICAL PRACTICE, 2006, 12 (06) : 601 - 612
  • [34] Unifying instrumental variable and inverse probability weighting approaches for inference of causal treatment effect and unmeasured confounding in observational studies
    Liu, Tao
    Hogan, Joseph W.
    STATISTICAL METHODS IN MEDICAL RESEARCH, 2021, 30 (03) : 671 - 686
  • [35] Testing Biased Randomization Assumptions and Quantifying Imperfect Matching and Residual Confounding in Matched Observational Studies
    Chen, Kan
    Heng, Siyu
    Long, Qi
    Zhang, Bo
    JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 2023, 32 (02) : 528 - 538
  • [36] Sensitivity analyses to estimate the potential impact of unmeasured confounding in causal research
    Groenwold, Rolf H. H.
    Nelson, David B.
    Nichol, Kristin L.
    Hoes, Arno W.
    Hak, Eelko
    INTERNATIONAL JOURNAL OF EPIDEMIOLOGY, 2010, 39 (01) : 107 - 117
  • [37] Adjusting for bias and unmeasured confounding in Mendelian randomization studies with binary responses
    Palmer, Tom M.
    Thompson, John R.
    Tobin, Martin D.
    Sheehan, Nuala A.
    Burton, Paul R.
    INTERNATIONAL JOURNAL OF EPIDEMIOLOGY, 2008, 37 (05) : 1161 - 1168
  • [38] Bisphosphonates and mortality: confounding in observational studies?
    Bergman, J.
    Nordstrom, A.
    Hommel, A.
    Kivipelto, M.
    Nordstrom, P.
    OSTEOPOROSIS INTERNATIONAL, 2019, 30 (10) : 1973 - 1982
  • [39] Bisphosphonates and mortality: confounding in observational studies?
    J. Bergman
    A. Nordström
    A. Hommel
    M. Kivipelto
    P. Nordström
    Osteoporosis International, 2019, 30 : 1973 - 1982
  • [40] Relevance of Controling for Confounding in Observational Studies
    Barreiro, Esther
    Munoz, Xavier
    Gonzalez-Barcala, Francisco-Javier
    Bustamante, Victor
    Ignacio de Granda-Orive, Jose
    ARCHIVOS DE BRONCONEUMOLOGIA, 2019, 55 (03): : 117 - 117