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Sim, Mikyung; Kim, Su-Young; Suh, Youngsuk – Educational and Psychological Measurement, 2022
Mediation models have been widely used in many disciplines to better understand the underlying processes between independent and dependent variables. Despite their popularity and importance, the appropriate sample sizes for estimating those models are not well known. Although several approaches (such as Monte Carlo methods) exist, applied…
Descriptors: Sample Size, Statistical Analysis, Predictor Variables, Path Analysis
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Hsiao, Yu-Yu; Kwok, Oi-Man; Lai, Mark H. C. – Educational and Psychological Measurement, 2018
Path models with observed composites based on multiple items (e.g., mean or sum score of the items) are commonly used to test interaction effects. Under this practice, researchers generally assume that the observed composites are measured without errors. In this study, we reviewed and evaluated two alternative methods within the structural…
Descriptors: Error of Measurement, Testing, Scores, Models
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Powell, Sarah R.; Cirino, Paul T.; Malone, Amelia S. – Exceptional Children, 2017
We identified child-level predictors of responsiveness to 2 types of mathematics intervention (calculation and word problem) among second-grade children with mathematics difficulty. Participants were 250 children in 107 classrooms in 23 schools pretested on mathematics and general cognitive measures and posttested on mathematics measures. We…
Descriptors: Intervention, Evidence Based Practice, Mathematics Instruction, Predictor Variables
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Luyten, Hans; de Wolf, Inge – School Effectiveness and School Improvement, 2011
This article focuses on the relation between student population characteristics and average test scores per school in the final grade of primary education from a dynamic perspective. Aggregated data of over 5,000 Dutch primary schools covering a 6-year period were used to study the relation between changes in school populations and shifts in mean…
Descriptors: Foreign Countries, Elementary Education, Elementary School Students, Disadvantaged