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Showing 1 to 15 of 23 results Save | Export
Fangxing Bai – ProQuest LLC, 2024
Mediation analyses are crucial for understanding the mechanisms through which interventions or theoretical constructs influence outcomes within nested structures, commonly found in education, psychology, and sociology. Recognizing the importance of these effects, designing and analyzing robust studies to detect them is essential. This dissertation…
Descriptors: Research Design, Experiments, Educational Research, Multivariate Analysis
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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
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Reza Norouzian; Zhouhan Jin; Stuart Webb – Modern Language Journal, 2025
Meta-analytic studies of second language (L2) learning typically employ a classic approach to meta-analysis. Although the classic approach can clarify findings, a multivariate, multilevel meta-analysis (3M) approach increases transparency by accounting for (a) dependencies in the evidence presented by primary studies, (b) methodological…
Descriptors: Meta Analysis, Multivariate Analysis, Notetaking, Second Language Learning
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Ting Ye; Ted Westling; Lindsay Page; Luke Keele – Grantee Submission, 2024
The clustered observational study (COS) design is the observational study counterpart to the clustered randomized trial. In a COS, a treatment is assigned to intact groups, and all units within the group are exposed to the treatment. However, the treatment is non-randomly assigned. COSs are common in both education and health services research. In…
Descriptors: Nonparametric Statistics, Identification, Causal Models, Multivariate Analysis
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Chan, Wendy; Hedges, Larry V.; Hedberg, E. C. – Journal of Experimental Education, 2022
Many experimental designs in educational and behavioral research involve at least one level of clustering. Clustering affects the precision of estimators and its impact on statistics in cross-sectional studies is well known. Clustering also occurs in longitudinal designs where students that are initially grouped may be regrouped in the following…
Descriptors: Educational Research, Multivariate Analysis, Longitudinal Studies, Effect Size
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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
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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
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Rhoads, Christopher – Journal of Educational and Behavioral Statistics, 2017
Researchers designing multisite and cluster randomized trials of educational interventions will usually conduct a power analysis in the planning stage of the study. To conduct the power analysis, researchers often use estimates of intracluster correlation coefficients and effect sizes derived from an analysis of survey data. When there is…
Descriptors: Statistical Analysis, Hierarchical Linear Modeling, Surveys, Effect Size
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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
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Stockard, Jean; Wood, Timothy W.; Coughlin, Cristy; Rasplica Khoury, Caitlin – Review of Educational Research, 2018
Quantitative mixed models were used to examine literature published from 1966 through 2016 on the effectiveness of Direct Instruction. Analyses were based on 328 studies involving 413 study designs and almost 4,000 effects. Results are reported for the total set and subareas regarding reading, math, language, spelling, and multiple or other…
Descriptors: Direct Instruction, Meta Analysis, Instructional Effectiveness, Educational Research
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Rhoads, Christopher – Journal of Research on Educational Effectiveness, 2014
Recent publications have drawn attention to the idea of utilizing prior information about the correlation structure to improve statistical power in cluster randomized experiments. Because power in cluster randomized designs is a function of many different parameters, it has been difficult for applied researchers to discern a simple rule explaining…
Descriptors: Correlation, Statistical Analysis, Multivariate Analysis, Research Design
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McNeish, Daniel – Review of Educational Research, 2017
In education research, small samples are common because of financial limitations, logistical challenges, or exploratory studies. With small samples, statistical principles on which researchers rely do not hold, leading to trust issues with model estimates and possible replication issues when scaling up. Researchers are generally aware of such…
Descriptors: Models, Statistical Analysis, Sampling, Sample Size
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Karakaya-Ozyer, Kubra; Aksu-Dunya, Beyza – International Journal of Research in Education and Science, 2018
Structural equation modeling (SEM) is one of the most popular multivariate statistical techniques in Turkish educational research. This study elaborates the SEM procedures employed by 75 educational research articles which were published from 2010 to 2015 in Turkey. After documenting and coding 75 academic papers, categorical frequencies and…
Descriptors: Literature Reviews, Structural Equation Models, Educational Technology, Multivariate Analysis
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Spybrook, Jessaca – Journal of Experimental Education, 2014
The Institute of Education Sciences has funded more than 100 experiments to evaluate educational interventions in an effort to generate scientific evidence of program effectiveness on which to base education policy and practice. In general, these studies are designed with the goal of having adequate statistical power to detect the average…
Descriptors: Intervention, Educational Research, Research Methodology, Statistical Analysis
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Ashworth, Kristen E.; Pullen, Paige C. – Learning Disability Quarterly, 2015
The purpose of this study was to compare the results of a regression discontinuity design (RDD) with those of an experimental design of a tiered vocabulary intervention for children at risk for reading disability to determine RDD's feasibility as a research methodology for this type of study. Researchers reanalyzed an archival dataset of a…
Descriptors: Vocabulary, Intervention, At Risk Students, Reading Difficulties
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