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Causal Mediation Analyses with Rank Preserving Models

Author

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  • Thomas R. Ten Have
  • Marshall M. Joffe
  • Kevin G. Lynch
  • Gregory K. Brown
  • Stephen A. Maisto
  • Aaron T. Beck

Abstract

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Suggested Citation

  • Thomas R. Ten Have & Marshall M. Joffe & Kevin G. Lynch & Gregory K. Brown & Stephen A. Maisto & Aaron T. Beck, 2007. "Causal Mediation Analyses with Rank Preserving Models," Biometrics, The International Biometric Society, vol. 63(3), pages 926-934, September.
    • Handle: RePEc:bla:biomet:v:63:y:2007:i:3:p:926-934
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2007.00766.x
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    References listed on IDEAS

    as
    1. Constantine E. Frangakis & Donald B. Rubin, 2002. "Principal Stratification in Causal Inference," Biometrics, The International Biometric Society, vol. 58(1), pages 21-29, March.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Markus Frölich & Martin Huber, 2017. "Direct and indirect treatment effects–causal chains and mediation analysis with instrumental variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1645-1666, November.
    2. Martin Huber & Michael Lechner & Giovanni Mellace, 2016. "The Finite Sample Performance of Estimators for Mediation Analysis Under Sequential Conditional Independence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 139-160, January.
    3. Stephens Alisa & Joffe Marshall & Keele Luke, 2016. "Generalized Structural Mean Models for Evaluating Depression as a Post-treatment Effect Modifier of a Jobs Training Intervention," Journal of Causal Inference, De Gruyter, vol. 4(2), pages 1-17, September.
    4. Martin Huber & Yu‐Chin Hsu & Ying‐Ying Lee & Layal Lettry, 2020. "Direct and indirect effects of continuous treatments based on generalized propensity score weighting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(7), pages 814-840, November.
    5. Hsu Yu-Chin & Huber Martin & Lai Tsung-Chih, 2019. "Nonparametric estimation of natural direct and indirect effects based on inverse probability weighting," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-20, January.
    6. Zhao, Yi & Luo, Xi, 2023. "Multilevel mediation analysis with structured unmeasured mediator-outcome confounding," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
    7. Martin Huber & Anna Solovyeva, 2020. "Direct and Indirect Effects under Sample Selection and Outcome Attrition," Econometrics, MDPI, vol. 8(4), pages 1-25, December.
    8. Martin A. Lindquist, 2012. "Functional Causal Mediation Analysis With an Application to Brain Connectivity," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(500), pages 1297-1309, December.
    9. Martin Huber & Michael Lechner & Giovanni Mellace, 2017. "Why Do Tougher Caseworkers Increase Employment? The Role of Program Assignment as a Causal Mechanism," The Review of Economics and Statistics, MIT Press, vol. 99(1), pages 180-183, March.
    10. Christian Dippel & Robert Gold & Stephan Heblich & Rodrigo Pinto, 2017. "Instrumental Variables and Causal Mechanisms: Unpacking the Effect of Trade on Workers and Voters," CESifo Working Paper Series 6816, CESifo.
    11. Jing Cheng & Dylan S. Small, 2021. "Semiparametric models and inference for the effect of a treatment when the outcome is nonnegative with clumping at zero," Biometrics, The International Biometric Society, vol. 77(4), pages 1187-1201, December.
    12. 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).
    13. Jing Huang & Ying Yuan & David Wetter, 2019. "Latent Class Dynamic Mediation Model with Application to Smoking Cessation Data," Psychometrika, Springer;The Psychometric Society, vol. 84(1), pages 1-18, March.
    14. Viviana Celli, 2022. "Causal mediation analysis in economics: Objectives, assumptions, models," Journal of Economic Surveys, Wiley Blackwell, vol. 36(1), pages 214-234, February.
    15. Huber, Martin, 2012. "Identifying causal mechanisms in experiments (primarily) based on inverse probability weighting," Economics Working Paper Series 1213, University of St. Gallen, School of Economics and Political Science, revised May 2013.
    16. Qingzhao Yu & Kaelen L. Medeiros & Xiaocheng Wu & Roxanne E. Jensen, 2018. "Nonlinear Predictive Models for Multiple Mediation Analysis: With an Application to Explore Ethnic Disparities in Anxiety and Depression Among Cancer Survivors," Psychometrika, Springer;The Psychometric Society, vol. 83(4), pages 991-1006, December.
    17. Laura Forastiere & Fabrizia Mealli & Tyler J. VanderWeele, 2016. "Identification and Estimation of Causal Mechanisms in Clustered Encouragement Designs: Disentangling Bed Nets Using Bayesian Principal Stratification," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 510-525, April.
    18. Helmut Farbmacher & Martin Huber & Lukáš Lafférs & Henrika Langen & Martin Spindler, 2022. "Causal mediation analysis with double machine learning [Mediation analysis via potential outcomes models]," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 277-300.
    19. Martin Huber & Lukáš Lafférs, 2022. "Bounds on direct and indirect effects under treatment/mediator endogeneity and outcome attrition," Econometric Reviews, Taylor & Francis Journals, vol. 41(10), pages 1141-1163, November.
    20. Joffe Marshall M & Small Dylan & Ten Have Thomas & Brunelli Steve & Feldman Harold I, 2008. "Extended Instrumental Variables Estimation for Overall Effects," The International Journal of Biostatistics, De Gruyter, vol. 4(1), pages 1-20, April.
    21. Cheng Zheng & Xiao-Hua Zhou, 2017. "Causal mediation analysis on failure time outcome without sequential ignorability," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(4), pages 533-559, October.
    22. Stephens Alisa & Joffe Marshall & Keele Luke, 2016. "Generalized Structural Mean Models for Evaluating Depression as a Post-treatment Effect Modifier of a Jobs Training Intervention," Journal of Causal Inference, De Gruyter, vol. 4(2), pages 1, September.
    23. repec:hhs:ifauwp:2025_012 is not listed on IDEAS

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