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Wan Nurfarahiyah Wan Liah; Hutkemri Zulnaidi; Husaina Banu Kenayathulla – International Journal of Educational Management, 2025
Purpose: This paper aims to examine the key domains and prevailing trends in the context of teacher effectiveness while proposing directions for future research in this area. Design/methodology/approach: Utilising the Science Citation Index Expanded and Social Sciences Citation Index databases within Scopus, covering the period from 2014 to 2024,…
Descriptors: Literature Reviews, Bibliometrics, Teacher Effectiveness, Educational Trends
Jona Lilienthal; Sibylle Sturtz; Christoph Schürmann; Matthias Maiworm; Christian Röver; Tim Friede; Ralf Bender – Research Synthesis Methods, 2024
In Bayesian random-effects meta-analysis, the use of weakly informative prior distributions is of particular benefit in cases where only a few studies are included, a situation often encountered in health technology assessment (HTA). Suggestions for empirical prior distributions are available in the literature but it is unknown whether these are…
Descriptors: Bayesian Statistics, Meta Analysis, Health Sciences, Technology
Sandra Jo Wilson; Brian Freeman; E. C. Hedberg – Grantee Submission, 2024
As reporting of effect sizes in evaluation studies has proliferated, researchers and consumers of research need tools for interpreting or benchmarking the magnitude of those effect sizes that are relevant to the intervention, target population, and outcome measure being considered. Similarly, researchers planning education studies with social and…
Descriptors: Benchmarking, Effect Size, Meta Analysis, Statistical Analysis
Ke-Hai Yuan; Ling Ling; Zhiyong Zhang – Grantee Submission, 2024
Data in social and behavioral sciences typically contain measurement errors and do not have predefined metrics. Structural equation modeling (SEM) is widely used for the analysis of such data, where the scales of the manifest and latent variables are often subjective. This article studies how the model, parameter estimates, their standard errors…
Descriptors: Structural Equation Models, Computation, Social Science Research, Error of Measurement
Ke-Hai Yuan; Ling Ling; Zhiyong Zhang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Data in social and behavioral sciences typically contain measurement errors and do not have predefined metrics. Structural equation modeling (SEM) is widely used for the analysis of such data, where the scales of the manifest and latent variables are often subjective. This article studies how the model, parameter estimates, their standard errors…
Descriptors: Structural Equation Models, Computation, Social Science Research, Error of Measurement