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Estimation of Indirect Effects in the Presence of Unmeasured Confounding for the Mediator–Outcome Relationship in a Multilevel 2-1-1 Mediation Model

Author

Listed:
  • Wouter Talloen
  • Beatrijs Moerkerke
  • Tom Loeys
  • Jessie De Naeghel
  • Hilde Van Keer
  • Stijn Vansteelandt

Abstract

To assess the direct and indirect effect of an intervention, multilevel 2-1-1 studies with intervention randomized at the upper (class) level and mediator and outcome measured at the lower (student) level are frequently used in educational research. In such studies, the mediation process may flow through the student-level mediator (the within indirect effect) or a class-aggregated mediator (the contextual indirect effect). In this article, we cast mediation analysis within the counterfactual framework and clarify the assumptions that are needed to identify the within and contextual indirect effect. We show that unlike the contextual indirect effect, the within indirect effect can be unbiasedly estimated in linear models in the presence of unmeasured confounders of the mediator–outcome relationship at the upper level that exert additive effects on mediator and outcome. When unmeasured confounding occurs at the individual level, both indirect effects are no longer identified. We propose sensitivity analyses to assess the robustness of the within and contextual indirect effect under lower and upper-level confounding, respectively.

Suggested Citation

  • Wouter Talloen & Beatrijs Moerkerke & Tom Loeys & Jessie De Naeghel & Hilde Van Keer & Stijn Vansteelandt, 2016. "Estimation of Indirect Effects in the Presence of Unmeasured Confounding for the Mediator–Outcome Relationship in a Multilevel 2-1-1 Mediation Model," Journal of Educational and Behavioral Statistics, , vol. 41(4), pages 359-391, August.
  • Handle: RePEc:sae:jedbes:v:41:y:2016:i:4:p:359-391
    DOI: 10.3102/1076998616636855
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    References listed on IDEAS

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    1. Tyler J. Vanderweele & Guanglei Hong & Stephanie M. Jones & Joshua L. Brown, 2013. "Mediation and Spillover Effects in Group-Randomized Trials: A Case Study of the 4Rs Educational Intervention," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(502), pages 469-482, June.
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    5. Croissant, Yves & Millo, Giovanni, 2008. "Panel Data Econometrics in R: The plm Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i02).
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