Lawrence T. DeCarlo’s recent article introduces a psychological framework for mixed-format exams, combining signal detection theory (SDT) for multiple-choice items and item response theory (IRT) for open-ended items. This fusion allows for a unified model that captures the nuances of each item type while providing insights into the underlying cognitive …
This article discusses a Bayesian hierarchical framework for the Two-Parameter Logistic (2PL) Item Response Theory (IRT) model. By introducing hierarchical priors for both respondent abilities and item parameters, this method offers a detailed perspective on latent traits. Additionally, the use of Automatic Differentiation Variational Inference (ADVI) makes the approach scalable …
The Dataset Generator available at Cogn-IQ.org is a powerful resource designed for researchers and practitioners working with Item Response Theory (IRT). This tool simulates datasets tailored for psychometric analysis, enabling users to explore a range of testing scenarios with customizable item and subject characteristics. It supports the widely used 2-Parameter …
