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R-package LNIRT for joint modeling of response accuracy and times.
Fox, Jean-Paul; Klotzke, Konrad; Simsek, Ahmet Salih.
Afiliação
  • Fox JP; Faculty of Behavioral, Management, and Social Sciences, University of Twente, Enschede, Netherlands.
  • Klotzke K; Faculty of Behavioral, Management, and Social Sciences, University of Twente, Enschede, Netherlands.
  • Simsek AS; Department of Measurement and Evaluation in Education, University of Kirsehir Ahi Evran, Kirsehir, Turkey.
PeerJ Comput Sci ; 9: e1232, 2023.
Article em En | MEDLINE | ID: mdl-37346642
ABSTRACT
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.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article