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On the Monotonicity of a Nondifferentially Mismeasured Binary Confounder

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  • Peña Jose M.

    (IDA, Linköping University, LinköpingSweden)

Abstract

Suppose that we are interested in the average causal effect of a binary treatment on an outcome when this relationship is confounded by a binary confounder. Suppose that the confounder is unobserved but a nondifferential proxy of it is observed. We show that, under certain monotonicity assumption that is empirically verifiable, adjusting for the proxy produces a measure of the effect that is between the unadjusted and the true measures.

Suggested Citation

  • Peña Jose M., 2020. "On the Monotonicity of a Nondifferentially Mismeasured Binary Confounder," Journal of Causal Inference, De Gruyter, vol. 8(1), pages 150-163, January.
    • Handle: RePEc:bpj:causin:v:8:y:2020:i:1:p:150-163:n:8
    DOI: 10.1515/jci-2020-0014
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    References listed on IDEAS

    as
    1. Elizabeth L. Ogburn & Tyler J. Vanderweele, 2013. "Bias attenuation results for nondifferentially mismeasured ordinal and coarsened confounders," Biometrika, Biometrika Trust, vol. 100(1), pages 241-248.
    2. Wang Miao & Zhi Geng & Eric J Tchetgen Tchetgen, 2018. "Identifying causal effects with proxy variables of an unmeasured confounder," Biometrika, Biometrika Trust, vol. 105(4), pages 987-993.
    3. Tyler J. VanderWeele & James M. Robins, 2010. "Signed directed acyclic graphs for causal inference," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(1), pages 111-127, January.
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    Cited by:

    1. Sjölander, Arvid & Peña, Jose M. & Gabriel, Erin E., 2022. "Bias results for nondifferential mismeasurement of a binary confounder," Statistics & Probability Letters, Elsevier, vol. 186(C).

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    More about this item

    Keywords

    average causal effect; confounding; monotonicity; 62D20; 62H22;
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