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Nianbo Dong; Benjamin Kelcey; Jessaca Spybrook – Journal of Experimental Education, 2024
Multisite cluster randomized trials (MCRTs), in which, the intermediate-level clusters (e.g., classrooms) are randomly assigned to the treatment or control condition within each site (e.g., school), are among the most commonly used experimental designs across a broad range of disciplines. MCRTs often align with the theory that programs are…
Descriptors: Research Design, Randomized Controlled Trials, Statistical Analysis, Sample Size
Regan Mozer; Luke Miratrix – Grantee Submission, 2024
For randomized trials that use text as an outcome, traditional approaches for assessing treatment impact require that each document first be manually coded for constructs of interest by trained human raters. This process, the current standard, is both time-consuming and limiting: even the largest human coding efforts are typically constrained to…
Descriptors: Artificial Intelligence, Coding, Efficiency, Statistical Inference
Kyle Cox; Ben Kelcey; Hannah Luce – Journal of Experimental Education, 2024
Comprehensive evaluation of treatment effects is aided by considerations for moderated effects. In educational research, the combination of natural hierarchical structures and prevalence of group-administered or shared facilitator treatments often produces three-level partially nested data structures. Literature details planning strategies for a…
Descriptors: Randomized Controlled Trials, Monte Carlo Methods, Hierarchical Linear Modeling, Educational Research
Eric C. Hedberg – Grantee Submission, 2023
In cluster randomized evaluations, a treatment or intervention is randomly assigned to a set of clusters each with constituent individual units of observations (e.g., student units that attend schools, which are assigned to treatment). One consideration of these designs is how many units are needed per cluster to achieve adequate statistical…
Descriptors: Statistical Analysis, Multivariate Analysis, Randomized Controlled Trials, Research Design
E. C. Hedberg – American Journal of Evaluation, 2023
In cluster randomized evaluations, a treatment or intervention is randomly assigned to a set of clusters each with constituent individual units of observations (e.g., student units that attend schools, which are assigned to treatment). One consideration of these designs is how many units are needed per cluster to achieve adequate statistical…
Descriptors: Statistical Analysis, Multivariate Analysis, Randomized Controlled Trials, Research Design
Li, Wei; Dong, Nianbo; Maynarad, Rebecca; Spybrook, Jessaca; Kelcey, Ben – Journal of Research on Educational Effectiveness, 2023
Cluster randomized trials (CRTs) are commonly used to evaluate educational interventions, particularly their effectiveness. Recently there has been greater emphasis on using these trials to explore cost-effectiveness. However, methods for establishing the power of cluster randomized cost-effectiveness trials (CRCETs) are limited. This study…
Descriptors: Research Design, Statistical Analysis, Randomized Controlled Trials, Cost Effectiveness
Benjamin Lu; Eli Ben-Michael; Avi Feller; Luke Miratrix – Journal of Educational and Behavioral Statistics, 2023
In multisite trials, learning about treatment effect variation across sites is critical for understanding where and for whom a program works. Unadjusted comparisons, however, capture "compositional" differences in the distributions of unit-level features as well as "contextual" differences in site-level features, including…
Descriptors: Statistical Analysis, Statistical Distributions, Program Implementation, Comparative Analysis
Xinran Li; Peng Ding; Donald B. Rubin – Grantee Submission, 2020
With many pretreatment covariates and treatment factors, the classical factorial experiment often fails to balance covariates across multiple factorial effects simultaneously. Therefore, it is intuitive to restrict the randomization of the treatment factors to satisfy certain covariate balance criteria, possibly conforming to the tiers of…
Descriptors: Experiments, Research Design, Randomized Controlled Trials, Sampling
Benjamin Lu; Eli Ben-Michael; Avi Feller; Luke Miratrix – Grantee Submission, 2022
In multisite trials, learning about treatment effect variation across sites is critical for understanding where and for whom a program works. Unadjusted comparisons, however, capture "compositional" differences in the distributions of unit-level features as well as "contextual" differences in site-level features, including…
Descriptors: Statistical Analysis, Statistical Distributions, Program Implementation, Comparative Analysis
Deke, John; Wei, Thomas; Kautz, Tim – National Center for Education Evaluation and Regional Assistance, 2017
Evaluators of education interventions are increasingly designing studies to detect impacts much smaller than the 0.20 standard deviations that Cohen (1988) characterized as "small." While the need to detect smaller impacts is based on compelling arguments that such impacts are substantively meaningful, the drive to detect smaller impacts…
Descriptors: Intervention, Educational Research, Research Problems, Statistical Bias
Fuchs, Lynn S.; Malone, Amelia S.; Schumacher, Robin F.; Namkung, Jessica; Wang, Amber – Grantee Submission, 2016
The purpose of this article was to summarize results from 5 randomized control trials assessing the effects of intervention to improve the fraction performance of 4th-grade students at-risk for difficulty in learning about fractions. We begin by explaining the importance of competence with fractions and why an instructional focus on fractions…
Descriptors: Mathematical Aptitude, Intervention, Fractions, Randomized Controlled Trials

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