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Do Typical RCTs of Education Interventions Have Sufficient Statistical Power for Linking Impacts on Teacher Practice and Student Achievement Outcomes?

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  • Peter Z. Schochet

Abstract

For randomized control trials (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 a study’s conceptual model is supported by data, and to identify mediators 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, and uses these formulas to conduct a simulated power analysis. The power analysis finds that for currently available mediators, the OLS approach will yield precise estimates of associations between teacher practice measures and student test score gains only if the sample contains about 150 to 200 study schools. The IV approach, which can adjust for potential omitted variable and simultaneity biases, has very little statistical power for mediator analyses. For typical RCT evaluations, these results may have design implications for the scope of the data collection effort for obtaining costly teacher practice mediators.

Suggested Citation

  • Peter Z. Schochet, 2009. "Do Typical RCTs of Education Interventions Have Sufficient Statistical Power for Linking Impacts on Teacher Practice and Student Achievement Outcomes?," Mathematica Policy Research Reports 8bb2ecd6a142422db269c1e0b, Mathematica Policy Research.
  • Handle: RePEc:mpr:mprres:8bb2ecd6a142422db269c1e0b9dec26f
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    References listed on IDEAS

    as
    1. Peter Z. Schochet, "undated". "Statistical Power for Random Assignment Evaluations of Education Programs (Journal Article)," Mathematica Policy Research Reports a110ff428db043f4a6f55d349, Mathematica Policy Research.
    2. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-529, October.
    3. repec:mpr:mprres:5863 is not listed on IDEAS
    4. Peter Z. Schochet, "undated". "Statistical Power for Random Assignment Evaluations of Education Programs," Mathematica Policy Research Reports 6749d31ad72d4acf988f7dce5, Mathematica Policy Research.
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