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On the Estimation Accuracy of Causal Effects using Supplementary Variables

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  • Manabu Kuroki
  • Takahiro Hayashi

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  • Manabu Kuroki & Takahiro Hayashi, 2016. "On the Estimation Accuracy of Causal Effects using Supplementary Variables," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 505-519, June.
    • Handle: RePEc:bla:scjsta:v:43:y:2016:i:2:p:505-519
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    File URL: http://hdl.handle.net/10.1111/sjos.12188
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    References listed on IDEAS

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    1. Zhihong Cai & Manabu Kuroki & Judea Pearl & Jin Tian, 2008. "Bounds on Direct Effects in the Presence of Confounded Intermediate Variables," Biometrics, The International Biometric Society, vol. 64(3), pages 695-701, September.
    2. Imai, Kosuke & Keele, Luke & Tingley, Dustin & Yamamoto, Teppei, 2011. "Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies," American Political Science Review, Cambridge University Press, vol. 105(4), pages 765-789, November.
    3. Manabu Kuroki & Judea Pearl, 2014. "Measurement bias and effect restoration in causal inference," Biometrika, Biometrika Trust, vol. 101(2), pages 423-437.
    4. Manabu Kuroki, 2007. "Graphical identifiability criteria for causal effects in studies with an unobserved treatment/response variable," Biometrika, Biometrika Trust, vol. 94(1), pages 37-47.
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    Cited by:

    1. Nanmo, Hisayoshi & Kuroki, Manabu, 2021. "Exact variance formula for the estimated mean outcome with external intervention based on the front-door criterion in Gaussian linear structural equation models," Journal of Multivariate Analysis, Elsevier, vol. 185(C).

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