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Shen, Zuchao; Kelcey, Benjamin – Journal of Research on Educational Effectiveness, 2022
Optimal sampling frameworks attempt to identify the most efficient sampling plans to achieve an adequate statistical power. Although such calculations are theoretical in nature, they are critical to the judicious and wise use of funding because they serve as important starting points that guide practical discussions around sampling tradeoffs and…
Descriptors: Sampling, Research Design, Randomized Controlled Trials, Statistical Analysis
Shen, Zuchao; Kelcey, Benjamin – Journal of Educational and Behavioral Statistics, 2020
Conventional optimal design frameworks consider a narrow range of sampling cost structures that thereby constrict their capacity to identify the most powerful and efficient designs. We relax several constraints of previous optimal design frameworks by allowing for variable sampling costs in cluster-randomized trials. The proposed framework…
Descriptors: Sampling, Research Design, Randomized Controlled Trials, Statistical Analysis
Shen, Zuchao; Kelcey, Benjamin; Cox, Kyle T.; Zhang, Jiaqi – AERA Online Paper Repository, 2017
Recent studies show cluster randomized trials may be well powered to detect mediation or indirect effects in multilevel settings. However, literature has rarely provided guidance on designing cluster-randomized trials aim to assess indirect effects. In this study, we developed closed-form expression to estimate the variance of and the statistical…
Descriptors: Randomized Controlled Trials, Research Design, Context Effect, Statistical Analysis