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Gamon Savatsomboon; Phamornpun Yurayat; Ong-art Chanprasitchai; Warawut Narkbunnum; Jibon Kumar Sharma; Surapol Svetsomboon – Journal of Practical Studies in Education, 2024
The paper has three major objectives. The first objective of the paper is to synthesize and define common categories of meta-analysis. The second objective is to propose a way to comprehend these common categories of meta-analysis through learning from their respective generic conceptual frameworks. The third objective is to point out which R…
Descriptors: Classification, Meta Analysis, Computer Software, Educational Research
Larini, Michel; Barthes, Angela – John Wiley & Sons, Inc, 2018
This book presents different data collection and representation techniques: elementary descriptive statistics, confirmatory statistics, multivariate approaches and statistical modeling. It exposes the possibility of giving more robustness to the classical methodologies of education sciences by adding a quantitative approach. The fundamentals of…
Descriptors: Statistical Analysis, Educational Research, Data Collection, Data Processing
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Perna, Laura W.; Leigh, Elaine W. – Educational Researcher, 2018
Over the past decade, but especially in the past few years, programs with a "promise" label have been advanced at the local, state, and federal levels. To advance understanding of the design, implementation, and impact of the many different versions of emerging programs, policymakers, practitioners, and researchers need an organizing…
Descriptors: Classification, College Programs, Multivariate Analysis, Policy Analysis
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Blackwell, Matthew; Honaker, James; King, Gary – Sociological Methods & Research, 2017
Although social scientists devote considerable effort to mitigating measurement error during data collection, they often ignore the issue during data analysis. And although many statistical methods have been proposed for reducing measurement error-induced biases, few have been widely used because of implausible assumptions, high levels of model…
Descriptors: Error of Measurement, Monte Carlo Methods, Data Collection, Simulation
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Blackwell, Matthew; Honaker, James; King, Gary – Sociological Methods & Research, 2017
We extend a unified and easy-to-use approach to measurement error and missing data. In our companion article, Blackwell, Honaker, and King give an intuitive overview of the new technique, along with practical suggestions and empirical applications. Here, we offer more precise technical details, more sophisticated measurement error model…
Descriptors: Error of Measurement, Correlation, Simulation, Bayesian Statistics
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Chernyavskaya, Yana S.; Kiselev, Sergey V.; Rassolov, Ilya M.; Kurushin, Viktor V.; Chernikova, Lyudmila I.; Faizova, Guzel R. – International Journal of Environmental and Science Education, 2016
The relevance of research: The relevance of the problem studied is caused by the acceleration of transition of the Russian economy on an innovative way of development, which depends on the vector of innovative sphere of services and, to a large extent, information and communication services, as well as it is caused by the poor drafting of…
Descriptors: Foreign Countries, Correlation, Cost Effectiveness, Factor Analysis
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Chiu, Chia-Yi; Köhn, Hans-Friedrich; Wu, Huey-Min – International Journal of Testing, 2016
The Reduced Reparameterized Unified Model (Reduced RUM) is a diagnostic classification model for educational assessment that has received considerable attention among psychometricians. However, the computational options for researchers and practitioners who wish to use the Reduced RUM in their work, but do not feel comfortable writing their own…
Descriptors: Educational Diagnosis, Classification, Models, Educational Assessment