Publication Date
In 2025 | 1 |
Since 2024 | 3 |
Since 2021 (last 5 years) | 21 |
Since 2016 (last 10 years) | 75 |
Since 2006 (last 20 years) | 204 |
Descriptor
Computation | 217 |
Models | 217 |
Statistical Analysis | 217 |
Item Response Theory | 42 |
Comparative Analysis | 37 |
Bayesian Statistics | 31 |
Correlation | 31 |
Monte Carlo Methods | 31 |
Simulation | 31 |
Scores | 30 |
Maximum Likelihood Statistics | 28 |
More ▼ |
Source
Author
Raykov, Tenko | 7 |
Krenzke, Tom | 5 |
Mohadjer, Leyla | 5 |
Cho, Sun-Joo | 4 |
Erciulescu, Andreea | 4 |
Fay, Robert | 4 |
Harring, Jeffrey R. | 4 |
Li, Jianzhu | 4 |
Marcoulides, George A. | 4 |
Ren, Weijia | 4 |
Schochet, Peter Z. | 4 |
More ▼ |
Publication Type
Education Level
Audience
Researchers | 2 |
Administrators | 1 |
Policymakers | 1 |
Teachers | 1 |
Location
Netherlands | 4 |
United Kingdom | 4 |
Australia | 3 |
California | 3 |
Massachusetts | 3 |
North Carolina | 3 |
Brazil | 2 |
Canada | 2 |
District of Columbia | 2 |
Germany | 2 |
Israel | 2 |
More ▼ |
Laws, Policies, & Programs
No Child Left Behind Act 2001 | 1 |
Race to the Top | 1 |
Assessments and Surveys
What Works Clearinghouse Rating
Roy Levy; Daniel McNeish – Journal of Educational and Behavioral Statistics, 2025
Research in education and behavioral sciences often involves the use of latent variable models that are related to indicators, as well as related to covariates or outcomes. Such models are subject to interpretational confounding, which occurs when fitting the model with covariates or outcomes alters the results for the measurement model. This has…
Descriptors: Models, Statistical Analysis, Measurement, Data Interpretation
Doran, Harold – Journal of Educational and Behavioral Statistics, 2023
This article is concerned with a subset of numerically stable and scalable algorithms useful to support computationally complex psychometric models in the era of machine learning and massive data. The subset selected here is a core set of numerical methods that should be familiar to computational psychometricians and considers whitening transforms…
Descriptors: Scaling, Algorithms, Psychometrics, Computation
Daza, Sebastian; Kreuger, L. Kurt – Sociological Methods & Research, 2021
Although agent-based models (ABMs) have been increasingly accepted in social sciences as a valid tool to formalize theory, propose mechanisms able to recreate regularities, and guide empirical research, we are not aware of any research using ABMs to assess the robustness of our statistical methods. We argue that ABMs can be extremely helpful to…
Descriptors: Statistical Analysis, Models, Selection, Social Influences
Rebeckah K. Fussell; Emily M. Stump; N. G. Holmes – Physical Review Physics Education Research, 2024
Physics education researchers are interested in using the tools of machine learning and natural language processing to make quantitative claims from natural language and text data, such as open-ended responses to survey questions. The aspiration is that this form of machine coding may be more efficient and consistent than human coding, allowing…
Descriptors: Physics, Educational Researchers, Artificial Intelligence, Natural Language Processing
Kenneth Tyler Wilcox; Ross Jacobucci; Zhiyong Zhang; Brooke A. Ammerman – Grantee Submission, 2023
Text is a burgeoning data source for psychological researchers, but little methodological research has focused on adapting popular modeling approaches for text to the context of psychological research. One popular measurement model for text, topic modeling, uses a latent mixture model to represent topics underlying a body of documents. Recently,…
Descriptors: Bayesian Statistics, Content Analysis, Undergraduate Students, Self Destructive Behavior
Thomas Mgonja; Francisco Robles – Journal of College Student Retention: Research, Theory & Practice, 2024
Completion of remedial mathematics has been identified as one of the keys to college success. However, completion rates in remedial mathematics have been low and are of much debate across America. This study leverages machine learning techniques in trying to predict and understand completion rates in remedial mathematics. The purpose of this study…
Descriptors: Predictor Variables, Remedial Mathematics, Mathematics Achievement, Graduation Rate
Blozis, Shelley A.; Harring, Jeffrey R. – Sociological Methods & Research, 2021
Nonlinear mixed-effects models are models in which one or more coefficients of the growth model enter in a nonlinear manner, such as appearing in the exponent of the growth function. In their applications, the within-individual residuals are often assumed to be independent with constant variance across time, an assumption that implies that the…
Descriptors: Statistical Analysis, Models, Computation, Goodness of Fit
Huang, Ao; Komukai, Sho; Friede, Tim; Hattori, Satoshi – Research Synthesis Methods, 2021
Prospective registration of study protocols in clinical trial registries is a useful way to minimize the risk of publication bias in meta-analysis, and several clinical trial registries are available nowadays. However, they are mainly used as a tool for searching studies and information submitted to the registries has not been utilized as…
Descriptors: Publications, Bias, Meta Analysis, Selection
Grund, Simon; Lüdtke, Oliver; Robitzsch, Alexander – Journal of Educational and Behavioral Statistics, 2023
Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…
Descriptors: Educational Research, Data Analysis, Error of Measurement, Computation
Goutte, Cyril; Durand, Guillaume – International Educational Data Mining Society, 2020
Learning curves are an important tool in cognitive diagnostics modeling to help assess how well students acquire new skills, and to refine and improve knowledge component models. Learning curves are typically obtained from a model estimated on real data obtained from a finite, and usually limited, sample of students. As a consequence, there is…
Descriptors: Learning, Models, Computation, Statistical Analysis
Lauren Kennedy; Andrew Gelman – Grantee Submission, 2021
Psychology research often focuses on interactions, and this has deep implications for inference from non-representative samples. For the goal of estimating average treatment effects, we propose to fit a model allowing treatment to interact with background variables and then average over the distribution of these variables in the population. This…
Descriptors: Models, Generalization, Psychological Studies, Computation
Li, Jianzhu; Krenzke, Tom; Ren, Weijia; Mohadjer, Leyla; Fay, Robert; Erciulescu, Andreea – National Center for Education Statistics, 2022
The Program for the International Assessment of Adult Competencies (PIAAC) is a multicycle international survey of adult skills and competencies sponsored by the Organization for Economic Cooperation and Development (OECD). The survey examines a range of basic skills in the information age and assesses these adult skills consistently across…
Descriptors: Adults, International Assessment, Adult Literacy, Numeracy
Erciulescu, Andreea; Ren, Weijia; Li, Jianzhu; Mohadjer, Leyla; Fay, Robert – National Center for Education Statistics, 2022
The Program for the International Assessment of Adult Competencies (PIAAC) is a multicycle survey of adult skills and competencies sponsored by the Organization for Economic Cooperation and Development (OECD). The survey examines a range of basic skills in the information age and assesses these adult skills consistently across participating…
Descriptors: Adults, International Assessment, Competence, Basic Skills
Tang, Xiaodan; Karabatsos, George; Chen, Haiqin – Applied Measurement in Education, 2020
In applications of item response theory (IRT) models, it is known that empirical violations of the local independence (LI) assumption can significantly bias parameter estimates. To address this issue, we propose a threshold-autoregressive item response theory (TAR-IRT) model that additionally accounts for order dependence among the item responses…
Descriptors: Item Response Theory, Test Items, Models, Computation
Dvir, Michal; Ben-Zvi, Dani – Instructional Science: An International Journal of the Learning Sciences, 2023
Estimating and accounting for statistical uncertainty have become essential in today's information age, and crucial for cultivating a sound decision making citizenry. Engaging with statistical uncertainty early on can support the gradual development of uncertainty-related considerations that are often challenging to foster at any age. Statistical…
Descriptors: Learning Processes, Computation, Numeracy, Attitudes