Statistical Power for Causally Defined Indirect Effects in Group-Randomized Trials With Individual-Level Mediators

Benjamin Kelcey, Nianbo Dong, Jessaca Spybrook and Kyle Cox
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Benjamin Kelcey: University of Cincinnati
Nianbo Dong: University of Missouri
Jessaca Spybrook: Western Michigan University
Kyle Cox: University of Cincinnati

Journal of Educational and Behavioral Statistics, 2017, vol. 42, issue 5, 499-530

Abstract: Designs that facilitate inferences concerning both the total and indirect effects of a treatment potentially offer a more holistic description of interventions because they can complement “what works†questions with the comprehensive study of the causal connections implied by substantive theories. Mapping the sensitivity of designs to detect these effects is of critical importance because it directly governs the types of evidence researchers can bring to bear on theories of action under realistic sample sizes. In this study, we develop closed-form expressions to estimate the variance of and the power to detect causally defined indirect effects in two-level group-randomized studies examining individual-level mediators (i.e., 2-1-1 mediation). We formulate our approach within the purview of typical multilevel mediation models and anchor their interpretation in the potential outcomes framework. The results provide power analysis formulas that reduce calculations to simple functions of the primary path coefficients (e.g., treatment–mediator and mediator–outcome relationships) and common summary statistics (e.g., intraclass correlation coefficients). Probing these formulas suggests that group-randomized designs can be well powered to detect indirect effects when carefully planned. The power formulas are implemented in the PowerUp software ( causalevaluation.org ).

Keywords: mediation; power; indirect effects; multilevel models; sample size determination (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:42:y:2017:i:5:p:499-530

DOI: 10.3102/1076998617695506

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