Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 4 |
| Since 2016 (last 10 years) | 6 |
| Since 2006 (last 20 years) | 6 |
Descriptor
Source
| Journal of Educational… | 2 |
| Journal of Educational and… | 2 |
| Grantee Submission | 1 |
| International Journal of… | 1 |
Author
| Anil, Duygu | 1 |
| Buyukatak, Emrah | 1 |
| Chen, Jianschen | 1 |
| Clifton, James P. | 1 |
| Cobb, Patrice R. | 1 |
| Depaoli, Sarah | 1 |
| Fujimoto, Ken A. | 1 |
| He, Qiwei | 1 |
| Jiao, Hong | 1 |
| Kaplan, David | 1 |
| Lyu, Weicong | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 5 |
| Reports - Research | 5 |
| Reports - Descriptive | 1 |
Education Level
| Secondary Education | 6 |
Audience
Location
| Turkey | 1 |
| United States | 1 |
Laws, Policies, & Programs
Assessments and Surveys
| Program for International… | 6 |
What Works Clearinghouse Rating
Peer reviewed
Download full text
Direct linkKaplan, David; Chen, Jianschen; Yavuz, Sinan; Lyu, Weicong – Grantee Submission, 2022
The purpose of this paper is to demonstrate and evaluate the use of "Bayesian dynamic borrowing"(Viele et al, in Pharm Stat 13:41-54, 2014) as a means of systematically utilizing historical information with specific applications to large-scale educational assessments. Dynamic borrowing via Bayesian hierarchical models is a special case…
Descriptors: Bayesian Statistics, Models, Prediction, Accuracy
Buyukatak, Emrah; Anil, Duygu – International Journal of Assessment Tools in Education, 2022
The purpose of this research was to determine classification accuracy of the factors affecting the success of students' reading skills based on PISA 2018 data by using Artificial Neural Networks, Decision Trees, K-Nearest Neighbor, and Naive Bayes data mining classification methods and to examine the general characteristics of success groups. In…
Descriptors: Classification, Accuracy, Reading Tests, Achievement Tests
Qiao, Xin; Jiao, Hong; He, Qiwei – Journal of Educational Measurement, 2023
Multiple group modeling is one of the methods to address the measurement noninvariance issue. Traditional studies on multiple group modeling have mainly focused on item responses. In computer-based assessments, joint modeling of response times and action counts with item responses helps estimate the latent speed and action levels in addition to…
Descriptors: Multivariate Analysis, Models, Item Response Theory, Statistical Distributions
Fujimoto, Ken A. – Journal of Educational Measurement, 2020
Multilevel bifactor item response theory (IRT) models are commonly used to account for features of the data that are related to the sampling and measurement processes used to gather those data. These models conventionally make assumptions about the portions of the data structure that represent these features. Unfortunately, when data violate these…
Descriptors: Bayesian Statistics, Item Response Theory, Achievement Tests, Secondary School Students
Trendtel, Matthias; Robitzsch, Alexander – Journal of Educational and Behavioral Statistics, 2021
A multidimensional Bayesian item response model is proposed for modeling item position effects. The first dimension corresponds to the ability that is to be measured; the second dimension represents a factor that allows for individual differences in item position effects called persistence. This model allows for nonlinear item position effects on…
Descriptors: Bayesian Statistics, Item Response Theory, Test Items, Test Format
Depaoli, Sarah; Clifton, James P.; Cobb, Patrice R. – Journal of Educational and Behavioral Statistics, 2016
A review of the software Just Another Gibbs Sampler (JAGS) is provided. We cover aspects related to history and development and the elements a user needs to know to get started with the program, including (a) definition of the data, (b) definition of the model, (c) compilation of the model, and (d) initialization of the model. An example using a…
Descriptors: Monte Carlo Methods, Markov Processes, Computer Software, Models
