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Abu-Ghalyoun, Omar – Educational Studies in Mathematics, 2021
Past studies have documented some pre-service teachers' (PSTs) difficulties in reasoning about sampling variability. This study adds to the body of literature by investigating the ideas that PSTs employ in reasoning about sampling variability, and by conjecturing what is behind the difficulties especially during the contextuality episodes. This…
Descriptors: Preservice Teachers, Abstract Reasoning, Sampling, Statistics Education
Almehrizi, Rashid S. – Journal of Educational Measurement, 2021
Estimates of various variance components, universe score variance, measurement error variances, and generalizability coefficients, like all statistics, are subject to sampling variability, particularly in small samples. Such variability is quantified traditionally through estimated standard errors and/or confidence intervals. The paper derived new…
Descriptors: Error of Measurement, Statistics, Design, Generalizability Theory
Siegel, Lianne; Murad, M. Hassan; Chu, Haitao – Research Synthesis Methods, 2021
Often clinicians are interested in determining whether a subject's measurement falls within a normal range, defined as a range of values of a continuous outcome which contains some proportion (eg, 95%) of measurements from a healthy population. Several studies in the biomedical field have estimated reference ranges based on a meta-analysis of…
Descriptors: Meta Analysis, Medical Research, Biomedicine, Bayesian Statistics
McDonald, Dale; Schultz, Margaret – National Catholic Educational Association, 2021
The latest edition highlights information about schools, enrollment and staffing patterns for Catholic elementary and secondary schools for the 2020-2021 school year. [For the 2019-2020 edition, see ED613136.]
Descriptors: Catholic Schools, Elementary Schools, Secondary Schools, Enrollment
Andrew Gelman; Matthijs Vákár – Grantee Submission, 2021
It is not always clear how to adjust for control data in causal inference, balancing the goals of reducing bias and variance. We show how, in a setting with repeated experiments, Bayesian hierarchical modeling yields an adaptive procedure that uses the data to determine how much adjustment to perform. The result is a novel analysis with increased…
Descriptors: Bayesian Statistics, Statistical Analysis, Efficiency, Statistical Inference
James Ohisei Uanhoro – ProQuest LLC, 2021
This dissertation is a collection of three papers. The first is a conceptual paper, followed by two data analysis papers. All three papers examine the connection between structural equation models and regression models, and how one may better learn, research and apply structural equation models when structural equation models are thought of as…
Descriptors: Structural Equation Models, Bayesian Statistics, Multiple Regression Analysis, Factor Analysis
Hashim, Shirin A.; Kelley-Kemple, Thomas; Laski, Mary E. – Annenberg Institute for School Reform at Brown University, 2023
We propose a new method for estimating school-level characteristics from publicly available census data. We use a school's location to impute its catchment area by aggregating the nearest "n" census block groups such that the number of school-aged children in those "n" block groups is just over the number of students enrolled…
Descriptors: Institutional Characteristics, Schools, Computation, Census Figures
Knezek, Gerald; Gibson, David; Christensen, Rhonda; Trevisan, Ottavia; Carter, Morgan – British Journal of Educational Technology, 2023
This article reports on a trace-based assessment of approaches to learning used by middle school aged children who interacted with NASA Mars Mission science, technology, engineering and mathematics (STEM) games in "Whyville," an online game environment with 8 million registered young learners. The learning objectives of two games…
Descriptors: Learning Analytics, Nonparametric Statistics, Multidimensional Scaling, STEM Education
Starkey, Louise; Yates, Anne; de Roiste, Mairead; Lundqvist, Karsten; Ormond, Adreanne; Randal, John; Sylvester, Allan – Educational Technology Research and Development, 2023
Disciplines in Higher Education have their own interpretations of what is essential knowledge that influences what is taught, how teaching occurs, and the role of digital tools. Disciplinary culture is dynamic and evolving, informed by disciplinary research and technology improvement. During the COVID-19 pandemic, digital solutions enabled ongoing…
Descriptors: Undergraduate Study, College Faculty, Educational Technology, Statistics
Wang, Ling Ling; Jian, Sun Xiao; Liu, Yan Lou; Xin, Tao – Applied Measurement in Education, 2023
Cognitive diagnostic assessment based on Bayesian networks (BN) is developed in this paper to evaluate student understanding of the physical concept of buoyancy. we propose a three-order granular-hierarchy BN model which accounts for both fine-grained attributes and high-level proficiencies. Conditional independence in the BN structure is tested…
Descriptors: Bayesian Statistics, Networks, Cognitive Measurement, Diagnostic Tests
von Davier, Matthias; Bezirhan, Ummugul – Educational and Psychological Measurement, 2023
Viable methods for the identification of item misfit or Differential Item Functioning (DIF) are central to scale construction and sound measurement. Many approaches rely on the derivation of a limiting distribution under the assumption that a certain model fits the data perfectly. Typical DIF assumptions such as the monotonicity and population…
Descriptors: Robustness (Statistics), Test Items, Item Analysis, Goodness of Fit
Gorney, Kylie; Wollack, James A.; Sinharay, Sandip; Eckerly, Carol – Journal of Educational and Behavioral Statistics, 2023
Any time examinees have had access to items and/or answers prior to taking a test, the fairness of the test and validity of test score interpretations are threatened. Therefore, there is a high demand for procedures to detect both compromised items (CI) and examinees with preknowledge (EWP). In this article, we develop a procedure that uses item…
Descriptors: Scores, Test Validity, Test Items, Prior Learning
Wallin, Gabriel; Wiberg, Marie – Journal of Educational and Behavioral Statistics, 2023
This study explores the usefulness of covariates on equating test scores from nonequivalent test groups. The covariates are captured by an estimated propensity score, which is used as a proxy for latent ability to balance the test groups. The objective is to assess the sensitivity of the equated scores to various misspecifications in the…
Descriptors: Models, Error of Measurement, Robustness (Statistics), Equated Scores
Hayes, William M.; Wedell, Douglas H. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2023
In reinforcement learning (RL) tasks, decision makers learn the values of actions in a context-dependent fashion. Although context dependence has many advantages, it can lead to suboptimal preferences when choice options are extrapolated beyond their original encoding contexts. Here, we tested whether we could manipulate context dependence in RL…
Descriptors: Reinforcement, Learning Processes, Attention, Context Effect
Yao, Minghong; Wang, Yuning; Ren, Yan; Jia, Yulong; Zou, Kang; Li, Ling; Sun, Xin – Research Synthesis Methods, 2023
Rare events meta-analyses of randomized controlled trials (RCTs) are often underpowered because the outcomes are infrequent. Real-world evidence (RWE) from non-randomized studies may provide valuable complementary evidence about the effects of rare events, and there is growing interest in including such evidence in the decision-making process.…
Descriptors: Evidence, Meta Analysis, Randomized Controlled Trials, Decision Making

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