Work

lsirm12pl: An R Package for the Latent Space Item Response Model

Year: 2025

Type: article

Abstract: 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 shared latent metric space. The R package lsirm12pl implements Bayesian estimation of the LSIRM and its extensions for various response types, base model specifications, and missing data handling. Furthermore, the lsirm12pl package provides methods to improve model utilization and interpretation, such as clustering item positions on an estimated interaction map. The package also offers convenient summary and plotting options to evaluate and process the estimated results. In this paper, we provide an overview of the LSIRM's methodological foundation and describe several extensions included in the package. We then demonstrate the use of the package with real data examples contained within it.

Source: The R Journal

DOI: 10.32614/rj-2025-021

Authors: Dongyoung Go, Gwanghee Kim, Jina Park, Junyong Park, Minjeong Jeon, Ick Hoon Jin

Institutions: Yonsei University, Samsung Electronics (South Korea)

Language: English

Topic: Psychometric Methodologies and Testing

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: diamond

Funders: National Research Foundation, Yonsei University, National Research Foundation of Korea, Institute for Information and Communications Technology Promotion