Publication Date
In 2025 | 0 |
Since 2024 | 2 |
Since 2021 (last 5 years) | 4 |
Since 2016 (last 10 years) | 5 |
Since 2006 (last 20 years) | 16 |
Descriptor
Computation | 16 |
Generalization | 16 |
Models | 16 |
Comparative Analysis | 4 |
Regression (Statistics) | 4 |
Bayesian Statistics | 3 |
Item Response Theory | 3 |
Prediction | 3 |
Simulation | 3 |
Statistical Analysis | 3 |
Age Differences | 2 |
More ▼ |
Source
Author
Alina A. Davier | 1 |
Andrew D. Ho | 1 |
Andrew Gelman | 1 |
Aseltine, Robert H., Jr. | 1 |
Barnes, Tiffany, Ed. | 1 |
Bergert, F. Bryan | 1 |
Botella, Juan | 1 |
Breier, Bernhard H. | 1 |
Calamaro, Shira | 1 |
Crawford, L. Elizabeth | 1 |
David Eby | 1 |
More ▼ |
Publication Type
Journal Articles | 13 |
Reports - Research | 8 |
Reports - Evaluative | 4 |
Reports - Descriptive | 3 |
Collected Works - Proceedings | 1 |
Education Level
Higher Education | 2 |
Secondary Education | 2 |
Early Childhood Education | 1 |
Elementary Education | 1 |
High Schools | 1 |
Junior High Schools | 1 |
Middle Schools | 1 |
Postsecondary Education | 1 |
Audience
Location
China | 1 |
Massachusetts | 1 |
Laws, Policies, & Programs
Assessments and Surveys
Big Five Inventory | 1 |
Center for Epidemiologic… | 1 |
What Works Clearinghouse Rating
Justin L. Kern – Journal of Educational and Behavioral Statistics, 2024
Given the frequent presence of slipping and guessing in item responses, models for the inclusion of their effects are highly important. Unfortunately, the most common model for their inclusion, the four-parameter item response theory model, potentially has severe deficiencies related to its possible unidentifiability. With this issue in mind, the…
Descriptors: Item Response Theory, Models, Bayesian Statistics, Generalization
Terry A. Ackerman; Deborah L. Bandalos; Derek C. Briggs; Howard T. Everson; Andrew D. Ho; Susan M. Lottridge; Matthew J. Madison; Sandip Sinharay; Michael C. Rodriguez; Michael Russell; Alina A. Davier; Stefanie A. Wind – Educational Measurement: Issues and Practice, 2024
This article presents the consensus of an National Council on Measurement in Education Presidential Task Force on Foundational Competencies in Educational Measurement. Foundational competencies are those that support future development of additional professional and disciplinary competencies. The authors develop a framework for foundational…
Descriptors: Educational Assessment, Competence, Skill Development, Communication Skills
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
Calamaro, Shira; Jarosz, Gaja – Cognitive Science, 2015
Phonological rules create alternations in the phonetic realizations of related words. These rules must be learned by infants in order to identify the phonological inventory, the morphological structure, and the lexicon of a language. Recent work proposes a computational model for the learning of one kind of phonological alternation, allophony…
Descriptors: Language Acquisition, Phonology, Models, Indo European Languages
Peter Organisciak; Michele Newman; David Eby; Selcuk Acar; Denis Dumas – Grantee Submission, 2023
Purpose: Most educational assessments tend to be constructed in a close-ended format, which is easier to score consistently and more affordable. However, recent work has leveraged computation text methods from the information sciences to make open-ended measurement more effective and reliable for older students. This study asks whether such text…
Descriptors: Learning Analytics, Child Language, Semantics, Age Differences
Jeon, Minjeong; Rijmen, Frank; Rabe-Hesketh, Sophia – Journal of Educational and Behavioral Statistics, 2013
The authors present a generalization of the multiple-group bifactor model that extends the classical bifactor model for categorical outcomes by relaxing the typical assumption of independence of the specific dimensions. In addition to the means and variances of all dimensions, the correlations among the specific dimensions are allowed to differ…
Descriptors: Test Bias, Generalization, Models, Item Response Theory
López-López, José Antonio; Botella, Juan; Sánchez-Meca, Julio; Marín-Martínez, Fulgencio – Journal of Educational and Behavioral Statistics, 2013
Since heterogeneity between reliability coefficients is usually found in reliability generalization studies, moderator analyses constitute a crucial step for that meta-analytic approach. In this study, different procedures for conducting mixed-effects meta-regression analyses were compared. Specifically, four transformation methods for the…
Descriptors: Reliability, Generalization, Meta Analysis, Regression (Statistics)
Yan, Jun; Aseltine, Robert H., Jr.; Harel, Ofer – Journal of Educational and Behavioral Statistics, 2013
Comparing regression coefficients between models when one model is nested within another is of great practical interest when two explanations of a given phenomenon are specified as linear models. The statistical problem is whether the coefficients associated with a given set of covariates change significantly when other covariates are added into…
Descriptors: Computation, Regression (Statistics), Comparative Analysis, Models
Fan, Yale – European Journal of Physics, 2011
We examine a generalization of the one-dimensional Ising model involving interactions among neighbourhoods of "k" adjacent spins. The model is solved by exploiting a connection to an interesting computational problem that we call ""k"-SAT on a ring", and is shown to be equivalent to the nearest-neighbour Ising model in the absence of an external…
Descriptors: Models, Science Instruction, College Science, Computation
Wang, Wen-Chung; Jin, Kuan-Yu – Applied Psychological Measurement, 2010
In this study, all the advantages of slope parameters, random weights, and latent regression are acknowledged when dealing with component and composite items by adding slope parameters and random weights into the standard item response model with internal restrictions on item difficulty and formulating this new model within a multilevel framework…
Descriptors: Test Items, Difficulty Level, Regression (Statistics), Generalization
Bergert, F. Bryan; Nosofsky, Robert M. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2007
The authors develop and test generalized versions of take-the-best (TTB) and rational (RAT) models of multiattribute paired-comparison inference. The generalized models make allowances for subjective attribute weighting, probabilistic orders of attribute inspection, and noisy decision making. A key new test involves a response-time (RT)…
Descriptors: Decision Making, Computation, Models, Reaction Time
Shiffrin, Richard M.; Lee, Michael D.; Kim, Woojae; Wagenmakers, Eric-Jan – Cognitive Science, 2008
This article reviews current methods for evaluating models in the cognitive sciences, including theoretically based approaches, such as Bayes factors and minimum description length measures; simulation approaches, including model mimicry evaluations; and practical approaches, such as validation and generalization measures. This article argues…
Descriptors: Bayesian Statistics, Generalization, Sciences, Models
Davison, Michael; Krageloh, Christian U.; Fraser, Mhoyra; Breier, Bernhard H. – Journal of the Experimental Analysis of Behavior, 2007
Two groups of 10 male rats were trained to nose poke for food pellets at four alternatives that provided differing rates of pellet delivery on aperiodic schedules. After a fixed number of pellets had been delivered, 5, 10 or 20 in different conditions of the experiment, a 10-s blackout occurred, and the locations of the differing rates of pellet…
Descriptors: Pregnancy, Computation, Nutrition, Mothers
Johnson, Timothy R. – Psychometrika, 2007
In this paper I present a class of discrete choice models for ordinal response variables based on a generalization of the stereotype model. The stereotype model can be derived and generalized as a random utility model for ordered alternatives. Random utility models can be specified to account for heteroscedastic and correlated utilities. In the…
Descriptors: Elementary School Students, Stereotypes, Response Style (Tests), Generalization
Duffy, Sean; Huttenlocher, Janellen; Crawford, L. Elizabeth – Developmental Science, 2006
The present study tests a model of category effects upon stimulus estimation in children. Prior work with adults suggests that people inductively generalize distributional information about a category of stimuli and use this information to adjust their estimates of individual stimuli in a way that maximizes average accuracy in estimation (see…
Descriptors: Classification, Computation, Visual Stimuli, Generalization
Previous Page | Next Page »
Pages: 1 | 2