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Liang, Xinya; Kamata, Akihito; Li, Ji – Educational and Psychological Measurement, 2020
One important issue in Bayesian estimation is the determination of an effective informative prior. In hierarchical Bayes models, the uncertainty of hyperparameters in a prior can be further modeled via their own priors, namely, hyper priors. This study introduces a framework to construct hyper priors for both the mean and the variance…
Descriptors: Bayesian Statistics, Randomized Controlled Trials, Effect Size, Sampling
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Hua, Youjia; Hinzman, Michelle; Yuan, Chengan; Balint Langel, Kinga – Exceptional Children, 2020
An emerging body of research suggests that incorporating randomization schemes in single-case research designs strengthens study internal validity and data evaluation. The purpose of this study was to test the utility and feasibility of a randomized alternating-treatment design in an investigation that compared the combined effects of vocabulary…
Descriptors: Comparative Analysis, Intervention, Reading Instruction, Randomized Controlled Trials
Spybrook, Jessaca; Zhang, Qi; Kelcey, Ben; Dong, Nianbo – Educational Evaluation and Policy Analysis, 2020
Over the past 15 years, we have seen an increase in the use of cluster randomized trials (CRTs) to test the efficacy of educational interventions. These studies are often designed with the goal of determining whether a program works, or answering the what works question. Recently, the goals of these studies expanded to include for whom and under…
Descriptors: Randomized Controlled Trials, Educational Research, Program Effectiveness, Intervention
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Cope, Shannon; Chan, Keith; Jansen, Jeroen P. – Research Synthesis Methods, 2020
Background: Network meta-analysis (NMA) of survival data with a multidimensional treatment effect has been introduced as an alternative to NMA based on the proportional hazards assumption. However, these flexible models have some limitations, such as the use of an approximate likelihood based on discrete hazards, rather than a likelihood for…
Descriptors: Multivariate Analysis, Meta Analysis, Network Analysis, Models
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What Works Clearinghouse, 2020
The What Works Clearinghouse (WWC) systematic review process is the basis of many of its products, enabling the WWC to use consistent, objective, and transparent standards and procedures in its reviews, while also ensuring comprehensive coverage of the relevant literature. The WWC systematic review process consists of five steps: (1) Developing…
Descriptors: Educational Research, Evaluation Methods, Research Reports, Standards
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Osenk, Ivana; Johnson, Catherine; Wade, Tracey D. – School Mental Health, 2023
Perfectionism has adverse impacts on mental health and academic outcomes. We evaluated a 5-lesson classroom intervention for young adolescents delivered by teachers for impact on perfectionism, well-being, self-compassion, academic motivation and negative affect, at post-intervention and 3-month follow-up. Classes (N = 636 students, M[subscript…
Descriptors: Personality Problems, Randomized Controlled Trials, Comparative Analysis, Academic Achievement
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Akansha Singh; Germaine Uwimpuhwe; Dimitrios Vallis; Nasima Akhter; Tahani Coolen-Maturi; Steve Higgins; Jochen Einbeck; Martin Culliney; Sean Demack – Education Endowment Foundation, 2023
The aim of this study was to investigate and empirically derive parameters commonly used for statistical power and sample size calculations to better inform future trial design. Towards achieving this aim, the research project leveraged the richness of the National Pupil Database (NPD) and the Education Endowment Foundation (EEF) Archive to: (1)…
Descriptors: Foreign Countries, Statistical Analysis, Sample Size, Educational Research
Joshua B. Gilbert; Luke W. Miratrix; Mridul Joshi; Benjamin W. Domingue – Annenberg Institute for School Reform at Brown University, 2024
Analyzing heterogeneous treatment effects (HTE) plays a crucial role in understanding the impacts of educational interventions. A standard practice for HTE analysis is to examine interactions between treatment status and pre-intervention participant characteristics, such as pretest scores, to identify how different groups respond to treatment.…
Descriptors: Causal Models, Item Response Theory, Statistical Inference, Psychometrics
Joshua B. Gilbert; James S. Kim; Luke W. Miratrix – Annenberg Institute for School Reform at Brown University, 2024
Longitudinal models of individual growth typically emphasize between-person predictors of change but ignore how growth may vary "within" persons because each person contributes only one point at each time to the model. In contrast, modeling growth with multi-item assessments allows evaluation of how relative item performance may shift…
Descriptors: Vocabulary Development, Item Response Theory, Test Items, Student Development
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Joshua B. Gilbert; James S. Kim; Luke W. Miratrix – Applied Measurement in Education, 2024
Longitudinal models typically emphasize between-person predictors of change but ignore how growth varies "within" persons because each person contributes only one data point at each time. In contrast, modeling growth with multi-item assessments allows evaluation of how relative item performance may shift over time. While traditionally…
Descriptors: Vocabulary Development, Item Response Theory, Test Items, Student Development
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Huang, Francis L. – Practical Assessment, Research & Evaluation, 2018
Among econometricians, instrumental variable (IV) estimation is a commonly used technique to estimate the causal effect of a particular variable on a specified outcome. However, among applied researchers in the social sciences, IV estimation may not be well understood. Although there are several IV estimation primers from different fields, most…
Descriptors: Computation, Statistical Analysis, Compliance (Psychology), Randomized Controlled Trials
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Sales, Adam C.; Pane, John F. – Journal of Research on Educational Effectiveness, 2021
Randomized evaluations of educational technology produce log data as a bi-product: highly granular data on student and teacher usage. These datasets could shed light on causal mechanisms, effect heterogeneity, or optimal use. However, there are methodological challenges: implementation is not randomized and is only defined for the treatment group,…
Descriptors: Educational Technology, Use Studies, Randomized Controlled Trials, Mathematics Curriculum
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Chan, Wendy; Oh, Jimin; Luo, Peihao – Journal of Research on Educational Effectiveness, 2021
Findings from experimental studies have increasingly been used to inform policy in school settings. Thus far, the populations in many of these studies are typically defined in a cross-sectional context; namely, the populations are defined in the same academic year in which the study took place or the population is defined at a fixed time point.…
Descriptors: Generalization, Research Design, Demography, Case Studies
Petscher, Yaacov; Schatschneider, Christopher – Educational and Psychological Measurement, 2019
Complex data structures are ubiquitous in psychological research, especially in educational settings. In the context of randomized controlled trials, students are nested in classrooms but may be cross-classified by other units, such as small groups. Furthermore, in many cases only some students may be nested within a unit while other students may…
Descriptors: Structural Equation Models, Causal Models, Randomized Controlled Trials, Hierarchical Linear Modeling
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Wadhwa, Mansi; Cook, Thomas D. – New Directions for Child and Adolescent Development, 2019
This chapter highlights the key assumptions underlying Randomized Control Trials (RCTs) and illustrates them with regard to the practice of RCTs in the realm of child and adolescent development. Given the prominence of RCTs in policy research, we analyze the possible ways in which these assumptions might not be met by single randomized…
Descriptors: Randomized Controlled Trials, Evidence Based Practice, Child Development, Adolescent Development
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