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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
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
Flunger, Barbara; Trautwein, Ulrich; Nagengast, Benjamin; Lüdtke, Oliver; Niggli, Alois; Schnyder, Inge – Journal of Experimental Education, 2021
The present study illustrates the utility of applying multilevel mixture models in educational research, using data on the homework behavior of 1,812 Swiss eighth-grade students in French as a second language. A previous person-centered study identified 5 homework learning types characterized by different patterns of high or low homework time and…
Descriptors: Foreign Countries, Middle School Students, Grade 8, Multivariate Analysis
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
Finch, W. Holmes – Journal of Experimental Education, 2016
Multivariate analysis of variance (MANOVA) is widely used in educational research to compare means on multiple dependent variables across groups. Researchers faced with the problem of missing data often use multiple imputation of values in place of the missing observations. This study compares the performance of 2 methods for combining p values in…
Descriptors: Multivariate Analysis, Educational Research, Error of Measurement, Research Problems
Huang, Francis L. – Journal of Experimental Education, 2016
Multilevel modeling has grown in use over the years as a way to deal with the nonindependent nature of observations found in clustered data. However, other alternatives to multilevel modeling are available that can account for observations nested within clusters, including the use of Taylor series linearization for variance estimation, the design…
Descriptors: Multivariate Analysis, Hierarchical Linear Modeling, Sample Size, Error of Measurement
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