NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing all 7 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Shen, Ting; Konstantopoulos, Spyros – Journal of Experimental Education, 2022
Large-scale education data are collected via complex sampling designs that incorporate clustering and unequal probability of selection. Multilevel models are often utilized to account for clustering effects. The probability weighted approach (PWA) has been frequently used to deal with the unequal probability of selection. In this study, we examine…
Descriptors: Data Collection, Educational Research, Hierarchical Linear Modeling, Bayesian Statistics
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Kaplan, David; Chen, Jianshen – Society for Research on Educational Effectiveness, 2013
The purpose of this study is to explore Bayesian model averaging in the propensity score context. Previous research on Bayesian propensity score analysis does not take into account model uncertainty. In this regard, an internally consistent Bayesian framework for model building and estimation must also account for model uncertainty. The…
Descriptors: Bayesian Statistics, Models, Probability, Monte Carlo Methods
Levy, Roy – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2014
Digital games offer an appealing environment for assessing student proficiencies, including skills and misconceptions in a diagnostic setting. This paper proposes a dynamic Bayesian network modeling approach for observations of student performance from an educational video game. A Bayesian approach to model construction, calibration, and use in…
Descriptors: Video Games, Educational Games, Bayesian Statistics, Observation
Peer reviewed Peer reviewed
Direct linkDirect link
Huang, Hung-Yu; Wang, Wen-Chung – Educational and Psychological Measurement, 2014
In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…
Descriptors: Item Response Theory, Hierarchical Linear Modeling, Computation, Test Reliability
Peer reviewed Peer reviewed
Direct linkDirect link
Bolfarine, Heleno; Bazan, Jorge Luis – Journal of Educational and Behavioral Statistics, 2010
A Bayesian inference approach using Markov Chain Monte Carlo (MCMC) is developed for the logistic positive exponent (LPE) model proposed by Samejima and for a new skewed Logistic Item Response Theory (IRT) model, named Reflection LPE model. Both models lead to asymmetric item characteristic curves (ICC) and can be appropriate because a symmetric…
Descriptors: Markov Processes, Item Response Theory, Bayesian Statistics, Monte Carlo Methods
Peer reviewed Peer reviewed
Direct linkDirect link
Braeken, Johan; Blömeke, Sigrid – Assessment & Evaluation in Higher Education, 2016
Using data from the international Teacher Education and Development Study: Learning to Teach Mathematics (TEDS-M), the measurement equivalence of teachers' beliefs across countries is investigated for the case of "mathematics-as-a fixed-ability". Measurement equivalence is a crucial topic in all international large-scale assessments and…
Descriptors: Comparative Analysis, Bayesian Statistics, Test Bias, Teacher Education
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Johnson, Matthew S.; Jenkins, Frank – ETS Research Report Series, 2005
Large-scale educational assessments such as the National Assessment of Educational Progress (NAEP) sample examinees to whom an exam will be administered. In most situations the sampling design is not a simple random sample and must be accounted for in the estimating model. After reviewing the current operational estimation procedure for NAEP, this…
Descriptors: Bayesian Statistics, Hierarchical Linear Modeling, National Competency Tests, Sampling