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Huibin Zhang; Zuchao Shen; Walter L. Leite – Journal of Experimental Education, 2025
Cluster-randomized trials have been widely used to evaluate the treatment effects of interventions on student outcomes. When interventions are implemented by teachers, researchers need to account for the nested structure in schools (i.e., students are nested within teachers nested within schools). Schools usually have a very limited number of…
Descriptors: Sample Size, Multivariate Analysis, Randomized Controlled Trials, Correlation
Steven Glazerman; Larissa Campuzano; Nancy Murray – Evaluation Review, 2025
Randomized experiments involving education interventions are typically implemented as cluster randomized trials, with schools serving as clusters. To design such a study, it is critical to understand the degree to which learning outcomes vary between versus within clusters (schools), specifically the intraclass correlation coefficient. It is also…
Descriptors: Educational Experiments, Foreign Countries, Educational Assessment, Research Design
Schochet, Peter Z. – Journal of Educational and Behavioral Statistics, 2020
This article discusses estimation of average treatment effects for randomized controlled trials (RCTs) using grouped administrative data to help improve data access. The focus is on design-based estimators, derived using the building blocks of experiments, that are conducive to grouped data for a wide range of RCT designs, including clustered and…
Descriptors: Randomized Controlled Trials, Data Analysis, Research Design, Multivariate Analysis
Heather C. Hill; Anna Erickson – Annenberg Institute for School Reform at Brown University, 2021
Poor program implementation constitutes one explanation for null results in trials of educational interventions. For this reason, researchers often collect data about implementation fidelity when conducting such trials. In this article, we document whether and how researchers report and measure program fidelity in recent cluster-randomized trials.…
Descriptors: Fidelity, Program Effectiveness, Multivariate Analysis, Randomized Controlled Trials
Uwimpuhwe, Germaine; Singh, Akansha; Higgins, Steve; Coux, Mickael; Xiao, ZhiMin; Shkedy, Ziv; Kasim, Adetayo – Journal of Experimental Education, 2022
Educational stakeholders are keen to know the magnitude and importance of different interventions. However, the way evidence is communicated to support understanding of the effectiveness of an intervention is controversial. Typically studies in education have used the standardised mean difference as a measure of the impact of interventions. This…
Descriptors: Program Effectiveness, Intervention, Multivariate Analysis, Bayesian Statistics
Cole, Russell; Deke, John; Seftor, Neil – Society for Research on Educational Effectiveness, 2016
The What Works Clearinghouse (WWC) maintains design standards to identify rigorous, internally valid education research. As education researchers advance new methodologies, the WWC must revise its standards to include an assessment of the new designs. Recently, the WWC has revised standards for two emerging study designs: regression discontinuity…
Descriptors: Educational Research, Research Design, Regression (Statistics), Multivariate Analysis
Schweig, Jonathan David; Pane, John F. – International Journal of Research & Method in Education, 2016
Demands for scientific knowledge of what works in educational policy and practice has driven interest in quantitative investigations of educational outcomes, and randomized controlled trials (RCTs) have proliferated under these conditions. In educational settings, even when individuals are randomized, both experimental and control students are…
Descriptors: Randomized Controlled Trials, Educational Research, Multivariate Analysis, Models
Stapleton, Laura M.; McNeish, Daniel M.; Yang, Ji Seung – Educational Psychologist, 2016
Multilevel models are often used to evaluate hypotheses about relations among constructs when data are nested within clusters (Raudenbush & Bryk, 2002), although alternative approaches are available when analyzing nested data (Binder & Roberts, 2003; Sterba, 2009). The overarching goal of this article is to suggest when it is appropriate…
Descriptors: Hierarchical Linear Modeling, Data Analysis, Statistical Data, Multivariate Analysis