Corpus ID: 88518088

A Confounding Bridge Approach for Double Negative Control Inference on Causal Effects (Supplement and Sample Codes are included)

@article{Miao2018ACB,
  title={A Confounding Bridge Approach for Double Negative Control Inference on Causal Effects (Supplement and Sample Codes are included)},
  author={W. Miao and Xu Shi and E. Tchetgen},
  journal={arXiv: Methodology},
  year={2018}
}
  • W. Miao, Xu Shi, E. Tchetgen
  • Published 2018
  • Psychology, Mathematics
  • arXiv: Methodology
  • Unmeasured confounding is a key challenge for causal inference. Negative control variables are widely available in observational studies. A negative control outcome is associated with the confounder but not causally affected by the exposure in view, and a negative control exposure is correlated with the primary exposure or the confounder but does not causally affect the outcome of interest. In this paper, we establish a framework to use them for unmeasured confounding adjustment. We introduce a… CONTINUE READING
    4 Citations

    Figures and Tables from this paper.

    An Introduction to Proximal Causal Learning
    • 2
    • Highly Influenced
    • PDF
    A Selective Review of Negative Control Methods in Epidemiology
    • 2
    • PDF
    Semiparametric proximal causal inference

    References

    SHOWING 1-10 OF 52 REFERENCES
    The Control Outcome Calibration Approach for Causal Inference With Unobserved Confounding
    • 42
    • Highly Influential
    • PDF
    A New Method for Partial Correction of Residual Confounding in Time-Series and Other Observational Studies
    • 19
    • Highly Influential
    • PDF
    On negative outcome control of unobserved confounding as a generalization of difference-in-differences.
    • 16
    Negative Controls: A Tool for Detecting Confounding and Bias in Observational Studies
    • 482
    • Highly Influential
    • PDF
    A Method for Detection of Residual Confounding in Time-series and Other Observational Studies
    • 56
    • Highly Influential
    Mendelian randomization as an instrumental variable approach to causal inference
    • 469
    • PDF
    Identifying Causal Effects With Proxy Variables of an Unmeasured Confounder
    • 46
    • PDF
    CONFOUNDER ADJUSTMENT IN MULTIPLE HYPOTHESIS TESTING.
    • 58
    • PDF
    Assessing Sensitivity to an Unobserved Binary Covariate in an Observational Study with Binary Outcome
    • 829
    • Highly Influential
    • PDF