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M-bias, Butterfly Bias, and Butterfly Bias with Correlated Causes – A Comment on Ding and Miratrix (2015)

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  • Thoemmes Felix

    (Human Development, Cornell University, MVR G62A, Ithaca, NY 14853, USA)

Abstract

Ding and Miratrix [1] recently concluded that adjustment on a pre-treatment covariate is almost always preferable to reduce bias. I extend the examined parameter space of the models considered by Ding and Miratrix, and consider slight extensions of their models as well. Similar to the conclusion by Pearl [7], I identify constellations in which bias due to adjustment, or failing to adjust is symmetrical, but also confirm some findings of Ding and Miratrix.

Suggested Citation

  • Thoemmes Felix, 2015. "M-bias, Butterfly Bias, and Butterfly Bias with Correlated Causes – A Comment on Ding and Miratrix (2015)," Journal of Causal Inference, De Gruyter, vol. 3(2), pages 253-258, September.
    • Handle: RePEc:bpj:causin:v:3:y:2015:i:2:p:253-258:n:9
    DOI: 10.1515/jci-2015-0012
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    Cited by:

    1. Allan Dafoe, 2018. "Nonparametric Identification of Causal Effects under Temporal Dependence," Sociological Methods & Research, , vol. 47(2), pages 136-168, March.

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