An efficient PG-INLA algorithm for the Bayesian inference of logistic item response models
In this paper, we propose a Bayesian PG-INLA algorithm which is tailored to both one-dimensional and multidimensional 2-PL IRT models. The proposed PG-INLA algorithm utilizes a computationally efficient data augmentation strategy via the Pólya-Gamma variables, which can avoid low computational effic...
Saved in:
Main Authors: | Xiaofan Lin, Yincai Tang |
---|---|
Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2025-01-01
|
Series: | Statistical Theory and Related Fields |
Subjects: | |
Online Access: | https://www.tandfonline.com/doi/10.1080/24754269.2024.2442174 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Item Characteristics of National Examination Council’s Economics Multiple-Choice Items: An Item Response Theory Exploration
by: Yusuf Olayinka Shogbesan
Published: (2024-04-01) -
This is EPIC: Extensive Periphery for Impact and Control to study seabird habitat loss in and around offshore wind farms combining a peripheral control area and Bayesian statistics
by: Anne Grundlehner, et al.
Published: (2025-03-01) -
Integration of item response theory in the development of PhET-based graphing lines worksheets for optimizing student algebra competence
by: Giyanti, et al.
Published: (2025-02-01) -
ITEM RESPONSE THEORY ANALYSIS ON STUDENT STATISTICAL LITERACY TESTS
by: Mila Yulia Herosian, et al.
Published: (2023-01-01) -
AN EFFICIENT ALGORITHM FOR MINING FREQUENT ITEM-SETS CONTAINING A CONSTRAINT SUBSET
by: Dương Văn Hải, et al.
Published: (2013-06-01)