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Distinguishing Between Cross- and Cluster-Level Mediation Processes in the Cluster Randomized Trial

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  • Keenan A. Pituch
  • Laura M. Stapleton

Abstract

For the cluster randomized trial, the treatment, implemented at the cluster level, may be hypothesized to impact a final outcome of interest via a mediating variable, with the mediator and outcome being measured typically at the participant level. Two opposing views—one that allows the mediation process to flow through a participant-level mediator and one that does not—have been presented in the literature. We integrate these perspectives and argue that it is the theoretical model and the nature of the mediating variable that determines whether the treatment effect may be mediated by a participant-level or only a cluster-level mediator in this design. An accompanying simulation study shows that when the mediation process is unnecessarily restricted to the cluster level, the power to detect the presence of mediation is substantially reduced.

Suggested Citation

  • Keenan A. Pituch & Laura M. Stapleton, 2012. "Distinguishing Between Cross- and Cluster-Level Mediation Processes in the Cluster Randomized Trial," Sociological Methods & Research, , vol. 41(4), pages 630-670, November.
    • Handle: RePEc:sae:somere:v:41:y:2012:i:4:p:630-670
    DOI: 10.1177/0049124112460380
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    References listed on IDEAS

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    1. Hong, Guanglei & Raudenbush, Stephen W., 2006. "Evaluating Kindergarten Retention Policy: A Case Study of Causal Inference for Multilevel Observational Data," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 901-910, September.
    2. Donner, A. & Klar, N., 2004. "Pitfalls of and Controversies in Cluster Randomization Trials," American Journal of Public Health, American Public Health Association, vol. 94(3), pages 416-422.
    3. Schwartz, S., 1994. "The fallacy of the ecological fallacy: The potential misuse of a concept and the consequences," American Journal of Public Health, American Public Health Association, vol. 84(5), pages 819-824.
    4. Yongyun Shin & Stephen W. Raudenbush, 2010. "A Latent Cluster-Mean Approach to the Contextual Effects Model With Missing Data," Journal of Educational and Behavioral Statistics, , vol. 35(1), pages 26-53, February.
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    Cited by:

    1. Josephy Haeike & Vansteelandt Stijn & Vanderhasselt Marie-Anne & Loeys Tom, 2015. "Within-Subject Mediation Analysis in AB/BA Crossover Designs," The International Journal of Biostatistics, De Gruyter, vol. 11(1), pages 1-22, May.

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