R-package LNIRT for joint modeling of response accuracy and times
 
Yazarlar (3)
Jean-Paul Fox
Universiteit Twente
Konrad Kloztke
Universiteit Twente
Doç. Dr. Ahmet Salih ŞİMŞEK Kırşehir Ahi Evran Üniversitesi, Türkiye
Makale Türü Açık Erişim Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
Dergi Adı PeerJ Computer Science (Q2)
Dergi ISSN 2376-5992 Wos Dergi Scopus Dergi
Dergi Tarandığı Indeksler SCI-Expanded
Makale Dili İngilizce Basım Tarihi 03-2023
Kabul Tarihi 12-04-2026 Yayınlanma Tarihi –
Cilt / Sayı / Sayfa 2023 / 1 / 1–33 DOI 10.7717/peerj-cs.1232
Makale Linki https://peerj.com/articles/cs-1232/
Özet
In computer-based testing it has become standard to collect response accuracy (RA) and response times (RTs) for each test item. IRT models are used to measure a latent variable (e.g., ability, intelligence) using the RA observations. The information in the RTs can help to improve routine operations in (educational) testing, and provide information about speed of working. In modern applications, the joint models are needed to integrate RT information in a test analysis. The R-package LNIRT supports fitting joint models through a user-friendly setup which only requires specifying RA, RT data, and the total number of Gibbs sampling iterations. More detailed specifications of the analysis are optional. The main results can be reported through the summary functions, but output can also be analysed with Markov chain Monte Carlo (MCMC) output tools (i.e., coda, mcmcse). The main functionality of the LNIRT package is illustrated with two real data applications.
Anahtar Kelimeler
IRT models | Joint models | MCMC | Model-fit tools | R-code | R-package LNIRT | RT models | Variable working-speed
BM Sürdürülebilir Kalkınma Amaçları
Atıf Sayıları
Google Scholar 20
Scopus 4
Web of Science 5
R-package LNIRT for joint modeling of response accuracy and times

Paylaş

İletişim
  • Kırşehir Ahi Evran Üniversitesi Bağbaşı Yerleşkesi, 40100, KIRŞEHİR \ TÜRKİYE
  • unis@ahievran.edu.tr
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