Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 1 |
Since 2016 (last 10 years) | 2 |
Since 2006 (last 20 years) | 5 |
Descriptor
Markov Processes | 9 |
Probability | 9 |
Computation | 6 |
Models | 6 |
Monte Carlo Methods | 5 |
Bayesian Statistics | 4 |
Item Response Theory | 4 |
Simulation | 4 |
Regression (Statistics) | 3 |
Statistical Analysis | 3 |
Data Analysis | 2 |
More ▼ |
Source
Journal of Educational and… | 9 |
Author
Johnson, Matthew S. | 2 |
Bartolucci, Francesco | 1 |
Chang, Hua-hua | 1 |
Culpepper, Steven Andrew | 1 |
Dunn, Michelle C. | 1 |
Fox, Jean-Paul | 1 |
Garrow, John R. | 1 |
Junker, Brian W. | 1 |
Kadane, Joseph B. | 1 |
Li, Xiao | 1 |
Pennoni, Fulvia | 1 |
More ▼ |
Publication Type
Journal Articles | 9 |
Reports - Research | 6 |
Reports - Evaluative | 2 |
Reports - Descriptive | 1 |
Education Level
Higher Education | 2 |
Grade 11 | 1 |
Postsecondary Education | 1 |
Audience
Location
Italy | 1 |
Netherlands | 1 |
Pennsylvania | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Li, Xiao; Xu, Hanchen; Zhang, Jinming; Chang, Hua-hua – Journal of Educational and Behavioral Statistics, 2023
The adaptive learning problem concerns how to create an individualized learning plan (also referred to as a learning policy) that chooses the most appropriate learning materials based on a learner's latent traits. In this article, we study an important yet less-addressed adaptive learning problem--one that assumes continuous latent traits.…
Descriptors: Learning Processes, Models, Algorithms, Individualized Instruction
Sweet, Tracy M. – Journal of Educational and Behavioral Statistics, 2015
Social networks in education commonly involve some form of grouping, such as friendship cliques or teacher departments, and blockmodels are a type of statistical social network model that accommodate these grouping or blocks by assuming different within-group tie probabilities than between-group tie probabilities. We describe a class of models,…
Descriptors: Social Networks, Statistical Analysis, Probability, Models
Bartolucci, Francesco; Pennoni, Fulvia; Vittadini, Giorgio – Journal of Educational and Behavioral Statistics, 2016
We extend to the longitudinal setting a latent class approach that was recently introduced by Lanza, Coffman, and Xu to estimate the causal effect of a treatment. The proposed approach enables an evaluation of multiple treatment effects on subpopulations of individuals from a dynamic perspective, as it relies on a latent Markov (LM) model that is…
Descriptors: Causal Models, Markov Processes, Longitudinal Studies, Probability
Culpepper, Steven Andrew – Journal of Educational and Behavioral Statistics, 2015
A Bayesian model formulation of the deterministic inputs, noisy "and" gate (DINA) model is presented. Gibbs sampling is employed to simulate from the joint posterior distribution of item guessing and slipping parameters, subject attribute parameters, and latent class probabilities. The procedure extends concepts in Béguin and Glas,…
Descriptors: Bayesian Statistics, Models, Sampling, Computation
Verkuilen, Jay; Smithson, Michael – Journal of Educational and Behavioral Statistics, 2012
Doubly bounded continuous data are common in the social and behavioral sciences. Examples include judged probabilities, confidence ratings, derived proportions such as percent time on task, and bounded scale scores. Dependent variables of this kind are often difficult to analyze using normal theory models because their distributions may be quite…
Descriptors: Responses, Regression (Statistics), Statistical Analysis, Models
Sinharay, Sandip; Johnson, Matthew S.; Williamson, David M. – Journal of Educational and Behavioral Statistics, 2003
Item families, which are groups of related items, are becoming increasingly popular in complex educational assessments. For example, in automatic item generation (AIG) systems, a test may consist of multiple items generated from each of a number of item models. Item calibration or scoring for such an assessment requires fitting models that can…
Descriptors: Test Items, Markov Processes, Educational Testing, Probability
Fox, Jean-Paul – Journal of Educational and Behavioral Statistics, 2005
The randomized response (RR) technique is often used to obtain answers on sensitive questions. A new method is developed to measure latent variables using the RR technique because direct questioning leads to biased results. Within the RR technique is the probability of the true response modeled by an item response theory (IRT) model. The RR…
Descriptors: Item Response Theory, Models, Probability, Markov Processes
Using Data Augmentation and Markov Chain Monte Carlo for the Estimation of Unfolding Response Models
Johnson, Matthew S.; Junker, Brian W. – Journal of Educational and Behavioral Statistics, 2003
Unfolding response models, a class of item response theory (IRT) models that assume a unimodal item response function (IRF), are often used for the measurement of attitudes. Verhelst and Verstralen (1993)and Andrich and Luo (1993) independently developed unfolding response models by relating the observed responses to a more common monotone IRT…
Descriptors: Markov Processes, Item Response Theory, Computation, Data Analysis
Dunn, Michelle C.; Kadane, Joseph B.; Garrow, John R. – Journal of Educational and Behavioral Statistics, 2003
This article addresses the relationship between academic achievement and the student characteristics of absence and mobility. Mobility is a measure of how often a student changes schools. Absence is how often a student misses class. Standardized test scores are used as proxies for academic achievement. A model for the full joint distribution of…
Descriptors: Standardized Tests, Academic Achievement, Probability, Student Mobility