collaborators

6 papers

stat.AP2026

Analyzing Process Data from Computer-Based Assessments: A Tutorial on Preprocessing, Feature Extraction, and Model-Based Inference

Daeun Hwangbo, Junyeong Park, Minjeong Jeon +1

Computer-based assessments routinely generate detailed interaction logs -- commonly referred to as process data -- that record every action a respondent performs during task comple…

stat.AP2026

Hierarchical Latent Space Item Response Model for Analyzing Mental Health Vulnerability of Elementary School Students in South Korea

Soyeon Park, Seoyoung Shin, Minjeong Jeon +2

Mental health difficulties among elementary school students represent a growing public health concern in South Korea, yet analytical tools for identifying school-specific vulnerabi…

stat.AP2026

Constructing Reliable Social Networks from Conversational Data: An Ensemble Prompt Engineering Approach with Uncertainty Quantification

Gwanghee Kim, Ick Hoon Jin, Minjeong Jeon

Conversational data are central to the study of interaction dynamics and social structures across psychological research. However, constructing structured social networks from unst…

stat.AP2025

Euclidean Ideal Point Estimation From Roll-Call Data via Distance-Based Bipartite Network Models

Seungju Lee, In Kyun Kim, Jong Hee Park +1

Conventional ideal point models rely on Gaussian or quadratic utility functions that violate the triangle inequality, producing non-metric distances that complicate geometric inter…

stat.AP2025

Analysis of Log Data from an International Online Educational Assessment System: A Multi-state Survival Modeling Approach to Reaction Time between and across Action Sequence

Jina Park, Ick Hoon Jin, Minjeong Jeon

With increasingly available computer-based or online assessments, researchers have shown keen interest in analyzing log data to improve our understanding of test takers' problem-so…

stat.ME2025

lsirm12pl: An R package for latent space item response modeling

Dongyoung Go, Gwanghee Kim, Jina Park +3

The item response model in latent space (LSIRM; Jeon et al., 2021) uncovers unobserved interactions between respondents and items in the item response data by embedding both in a s…