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Mingya Huang; David Kaplan – Journal of Educational and Behavioral Statistics, 2025
The issue of model uncertainty has been gaining interest in education and the social sciences community over the years, and the dominant methods for handling model uncertainty are based on Bayesian inference, particularly, Bayesian model averaging. However, Bayesian model averaging assumes that the true data-generating model is within the…
Descriptors: Bayesian Statistics, Hierarchical Linear Modeling, Statistical Inference, Predictor Variables
Sainan Xu; Jing Lu; Jiwei Zhang; Chun Wang; Gongjun Xu – Grantee Submission, 2024
With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…
Descriptors: Educational Assessment, Bayesian Statistics, Statistical Inference, Item Response Theory
Depaoli, Sarah; Clifton, James P.; Cobb, Patrice R. – Journal of Educational and Behavioral Statistics, 2016
A review of the software Just Another Gibbs Sampler (JAGS) is provided. We cover aspects related to history and development and the elements a user needs to know to get started with the program, including (a) definition of the data, (b) definition of the model, (c) compilation of the model, and (d) initialization of the model. An example using a…
Descriptors: Monte Carlo Methods, Markov Processes, Computer Software, Models
Kaplan, David; McCarty, Alyn Turner – Large-scale Assessments in Education, 2013
Background: In the context of international large scale assessments, it is often not feasible to implement a complete survey of all relevant populations. For example, the OECD Program for International Student Assessment surveys both students and schools, but does not obtain information from teachers. In contrast the OECD Teaching and Learning…
Descriptors: Measurement, International Assessment, Student Surveys, Teacher Surveys

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