2011
DOI: 10.3102/1076998610375840
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Do Typical RCTs of Education Interventions Have Sufficient Statistical Power for Linking Impacts on Teacher Practice and Student Achievement Outcomes?

Abstract: For RCTs of education interventions, it is often of interest to estimate associations between student and mediating teacher practice outcomes, to examine the extent to which the study's conceptual model is supported by the data, and to identify specific mediators that are most associated with student learning. This paper develops statistical power formulas for such exploratory analyses under clustered school-based RCTs using ordinary least squares (OLS) and instrumental variable (IV) estimators U.S. Department… Show more

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Cited by 18 publications
(13 citation statements)
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“…Yet, substantive literature has emphasized that the benefits of studying theories, interventions, and intermediate processes are not limited to large-scale studies—small- to moderate-scale studies offer critical contributions to theory and social issues when they are well executed (e.g., Bodner & Bliese, 2018; Walton, 2014). In many areas of research, samples of fewer than 80 organizations are typical and samples greater than 80 may be considered prohibitively large (e.g., Schochet, 2011; Spybrook, Shi, & Kelcey, 2016). Perhaps because of the mismatch between the scale of many multilevel studies and the large-scale requirements of ML estimation in MLSEM, literature reviews have reported a widespread absence in the appropriate adjustment for measurement error (e.g., Aguinis, Edwards, & Bradley, 2017).…”
mentioning
confidence: 99%
“…Yet, substantive literature has emphasized that the benefits of studying theories, interventions, and intermediate processes are not limited to large-scale studies—small- to moderate-scale studies offer critical contributions to theory and social issues when they are well executed (e.g., Bodner & Bliese, 2018; Walton, 2014). In many areas of research, samples of fewer than 80 organizations are typical and samples greater than 80 may be considered prohibitively large (e.g., Schochet, 2011; Spybrook, Shi, & Kelcey, 2016). Perhaps because of the mismatch between the scale of many multilevel studies and the large-scale requirements of ML estimation in MLSEM, literature reviews have reported a widespread absence in the appropriate adjustment for measurement error (e.g., Aguinis, Edwards, & Bradley, 2017).…”
mentioning
confidence: 99%
“…There are several approaches to assessing mediation, including use of instrumental variables, (Bloom 2005a), and regression-based approaches that assess the relationship between the program and outcome through an indirect “mediated” path, and a direct effect from program to outcome (Baron and Kenny, 1986; Krull and MacKinnon, 2001). Both methods share the problem of having limited statistical power, and this is especially problematic if the mediator is at the cluster level (Schochet, 2009). This is the case of the iRAISE evaluation with teachers (clusters) randomized, instruction being the mediator, and student achievement the distal outcome.…”
Section: Data Sources and Resultsmentioning
confidence: 99%
“…There is a growing recognition of the critical contributions provided by study designs that facilitate inferences concerning both the total and indirect effects of a treatment (Institute of Educational Sciences, U.S. Department of Education, & National Science Foundation, 2013; Schochet, 2011; Sobel, 2008). Designs that facilitate both types of inferences potentially offer a more holistic and richer description of the programs under study and their guiding theories because they can complement “what works” type questions with the comprehensive study of the specific causal connections implied by program theories (Raudenbush & Sadoff, 2008).…”
mentioning
confidence: 99%
“…When data are structured hierarchically, a prominent design to facilitate inferences concerning the total and indirect effects is the group-randomized trial (e.g., Schochet, 2011). In this design, groups are randomly assigned to treatment conditions to assess the treatment's impact on an outcome and, when a mediator is observed, to probe the extent to which this impact flows through a mediating or intermediate variable implied by theory.…”
mentioning
confidence: 99%
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