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Causal mediation analysis with multiple mediators

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  • R. M. Daniel
  • B. L. De Stavola
  • S. N. Cousens
  • S. Vansteelandt

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  • R. M. Daniel & B. L. De Stavola & S. N. Cousens & S. Vansteelandt, 2015. "Causal mediation analysis with multiple mediators," Biometrics, The International Biometric Society, vol. 71(1), pages 1-14, March.
    • Handle: RePEc:bla:biomet:v:71:y:2015:i:1:p:1-14
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    References listed on IDEAS

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    1. Michael J. Daniels & Jason A. Roy & Chanmin Kim & Joseph W. Hogan & Michael G. Perri, 2012. "Bayesian Inference for the Causal Effect of Mediation," Biometrics, The International Biometric Society, vol. 68(4), pages 1028-1036, December.
    2. Rhian M. Daniel & Bianca L. De Stavola & Simon N. Cousens, 2011. "gformula: Estimating causal effects in the presence of time-varying confounding or mediation using the g-computation formula," Stata Journal, StataCorp LP, vol. 11(4), pages 479-517, December.
    3. Zheng Wenjing & van der Laan Mark J., 2012. "Targeted Maximum Likelihood Estimation of Natural Direct Effects," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-40, January.
    4. Jeffrey M. Albert & Suchitra Nelson, 2011. "Generalized Causal Mediation Analysis," Biometrics, The International Biometric Society, vol. 67(3), pages 1028-1038, September.
    5. Imai, Kosuke & Yamamoto, Teppei, 2013. "Identification and Sensitivity Analysis for Multiple Causal Mechanisms: Revisiting Evidence from Framing Experiments," Political Analysis, Cambridge University Press, vol. 21(2), pages 141-171, April.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Steen, Johan & Loeys, Tom & Moerkerke, Beatrijs & Vansteelandt, Stijn, 2017. "medflex: An R Package for Flexible Mediation Analysis using Natural Effect Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 76(i11).
    2. Ryan M. Andrews & Ilya Shpitser & Oscar Lopez & William T. Longstreth & Paulo H. M. Chaves & Lewis Kuller & Michelle C. Carlson, 2020. "Examining the causal mediating role of brain pathology on the relationship between diabetes and cognitive impairment: the Cardiovascular Health Study," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1705-1726, October.
    3. Guanglei Hong & Fan Yang & Xu Qin, 2023. "Posttreatment confounding in causal mediation studies: A cutting‐edge problem and a novel solution via sensitivity analysis," Biometrics, The International Biometric Society, vol. 79(2), pages 1042-1056, June.
    4. Qi Zhang, 2022. "High-Dimensional Mediation Analysis with Applications to Causal Gene Identification," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 14(3), pages 432-451, December.
    5. Haiyan Liu & Ick Hoon Jin & Zhiyong Zhang & Ying Yuan, 2021. "Social Network Mediation Analysis: A Latent Space Approach," Psychometrika, Springer;The Psychometric Society, vol. 86(1), pages 272-298, March.
    6. Vanessa Didelez, 2019. "Defining causal mediation with a longitudinal mediator and a survival outcome," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(4), pages 593-610, October.
    7. Tyler J. VanderWeele & Eric J. Tchetgen Tchetgen, 2017. "Mediation analysis with time varying exposures and mediators," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(3), pages 917-938, June.
    8. Zhao, Yi & Luo, Xi, 2023. "Multilevel mediation analysis with structured unmeasured mediator-outcome confounding," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
    9. Wen Wei Loh & Beatrijs Moerkerke & Tom Loeys & Stijn Vansteelandt, 2022. "Nonlinear mediation analysis with high‐dimensional mediators whose causal structure is unknown," Biometrics, The International Biometric Society, vol. 78(1), pages 46-59, March.
    10. Haoyu Wei & Hengrui Cai & Chengchun Shi & Rui Song, 2024. "On Efficient Inference of Causal Effects with Multiple Mediators," Papers 2401.05517, arXiv.org.
    11. Yanyi Song & Xiang Zhou & Min Zhang & Wei Zhao & Yongmei Liu & Sharon L. R. Kardia & Ana V. Diez Roux & Belinda L. Needham & Jennifer A. Smith & Bhramar Mukherjee, 2020. "Bayesian shrinkage estimation of high dimensional causal mediation effects in omics studies," Biometrics, The International Biometric Society, vol. 76(3), pages 700-710, September.
    12. Victor Quintas-Martinez & Mohammad Taha Bahadori & Eduardo Santiago & Jeff Mu & Dominik Janzing & David Heckerman, 2024. "Multiply-Robust Causal Change Attribution," Papers 2404.08839, arXiv.org, revised Sep 2024.
    13. Marco Doretti & Martina Raggi & Elena Stanghellini, 2022. "Exact parametric causal mediation analysis for a binary outcome with a binary mediator," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(1), pages 87-108, March.
    14. Admassu N. Lamu & Jan Abel Olsen, 2018. "Yes, health is important, but as much for its importance via social life: The direct and indirect effects of health on subjective well‐being in chronically ill individuals," Health Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 209-222, January.
    15. Xu Qin & Jonah Deutsch & Guanglei Hong, 2021. "Unpacking Complex Mediation Mechanisms And Their Heterogeneity Between Sites In A Job Corps Evaluation," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 40(1), pages 158-190, January.
    16. Soojin Park & Peter M. Steiner & David Kaplan, 2018. "Identification and Sensitivity Analysis for Average Causal Mediation Effects with Time-Varying Treatments and Mediators: Investigating the Underlying Mechanisms of Kindergarten Retention Policy," Psychometrika, Springer;The Psychometric Society, vol. 83(2), pages 298-320, June.
    17. Cai, Xizhen & Zhu, Yeying & Huang, Yuan & Ghosh, Debashis, 2022. "High-dimensional causal mediation analysis based on partial linear structural equation models," Computational Statistics & Data Analysis, Elsevier, vol. 174(C).
    18. Xiang Zhou, 2022. "Semiparametric estimation for causal mediation analysis with multiple causally ordered mediators," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(3), pages 794-821, July.

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