IDEAS home Printed from https://ideas.repec.org/a/taf/jnlasa/v108y2013i502p469-482.html
   My bibliography  Save this article

Mediation and Spillover Effects in Group-Randomized Trials: A Case Study of the 4Rs Educational Intervention

Author

Listed:
  • Tyler J. Vanderweele
  • Guanglei Hong
  • Stephanie M. Jones
  • Joshua L. Brown

Abstract

Peer influence and social interactions can give rise to spillover effects in which the exposure of one individual may affect outcomes of other individuals. Even if the intervention under study occurs at the group or cluster level as in group-randomized trials, spillover effects can occur when the mediator of interest is measured at a lower level than the treatment. Evaluators who choose groups rather than individuals as experimental units in a randomized trial often anticipate that the desirable changes in targeted social behaviors will be reinforced through interference among individuals in a group exposed to the same treatment. In an empirical evaluation of the effect of a school-wide intervention on reducing individual students' depressive symptoms, schools in matched pairs were randomly assigned to the 4Rs intervention or the control condition. Class quality was hypothesized as an important mediator assessed at the classroom level. We reason that the quality of one classroom may affect outcomes of children in another classroom because children interact not simply with their classmates but also with those from other classes in the hallways or on the playground. In investigating the role of class quality as a mediator, failure to account for such spillover effects of one classroom on the outcomes of children in other classrooms can potentially result in bias and problems with interpretation. Using a counterfactual conceptualization of direct, indirect, and spillover effects, we provide a framework that can accommodate issues of mediation and spillover effects in group randomized trials. We show that the total effect can be decomposed into a natural direct effect, a within-classroom mediated effect, and a spillover mediated effect. We give identification conditions for each of the causal effects of interest and provide results on the consequences of ignoring "interference" or "spillover effects" when they are in fact present. Our modeling approach disentangles these effects. The analysis examines whether the 4Rs intervention has an effect on childrens' depressive symptoms through changing the quality of other classes as well as through changing the quality of a child's own class. Supplementary materials for this article are available online.

Suggested Citation

  • 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.
  • Handle: RePEc:taf:jnlasa:v:108:y:2013:i:502:p:469-482
    DOI: 10.1080/01621459.2013.779832
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/01621459.2013.779832
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/01621459.2013.779832?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Luke Keele & Rocío Titiunik, 2018. "Geographic Natural Experiments with Interference: The Effect of All-Mail Voting on Turnout in Colorado," CESifo Economic Studies, CESifo Group, vol. 64(2), pages 127-149.
    2. Xu Qin & Guanglei Hong, 2017. "A Weighting Method for Assessing Between-Site Heterogeneity in Causal Mediation Mechanism," Journal of Educational and Behavioral Statistics, , vol. 42(3), pages 308-340, June.
    3. 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.
    4. 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.
    5. WenWu Wang & Ping Yu, 2023. "Nonequivalence of two least-absolute-deviation estimators for mediation effects," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(1), pages 370-387, March.
    6. Karim Anaya‐Izquierdo & Neal Alexander, 2021. "Spatial regression and spillover effects in cluster randomized trials with count outcomes," Biometrics, The International Biometric Society, vol. 77(2), pages 490-505, June.
    7. Weihua An & Tyler J. VanderWeele, 2022. "Opening the Blackbox of Treatment Interference: Tracing Treatment Diffusion through Network Analysis," Sociological Methods & Research, , vol. 51(1), pages 141-164, February.
    8. Sheetal Sharma & Edwin van Teijlingen & José M Belizán & Vanora Hundley & Padam Simkhada & Elisa Sicuri, 2016. "Measuring What Works: An Impact Evaluation of Women’s Groups on Maternal Health Uptake in Rural Nepal," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-16, May.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:jnlasa:v:108:y:2013:i:502:p:469-482. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/UASA20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.