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September 14, 2026International Journal of Testing

Development and application of graded response model incorporating response times

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Authors

CQChunying QinZLZhicheng LiuZLZhaosheng Luo

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Overview

Psychometric simulation study demonstrates reliable ability estimation in educational testing, suggesting that joint response time modeling improves polytomous assessment accuracy.

Key Points

  • Develop and evaluate a joint graded response model incorporating continuous response times (GRM-RT) within a hierarchical Bayesian framework to improve polytomous test scoring.
  • Formulated the GRM-RT model to jointly integrate continuous response times and polytomous categorical responses.
  • Conducted Monte Carlo simulations across systematically varied sample sizes (N=200, 500, 1000) and test lengths (M=10, 20, 40) to evaluate parameter recovery.
  • Applied the model to an empirical assessment dataset to confirm real-world utility.
  • Simulations demonstrated robust and stable parameter recovery across all evaluated sample size and test length conditions.
  • Parameter estimation precision improved progressively with larger sample sizes (N=1000) and longer test lengths (M=40).

Cite This Study

Qin et al. (2026) studied this question.

synapsesocial.com/papers/6aa7b3fc0926e14a848b35d2https://doi.org/10.1080/15305058.2026.2728577
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Bayesian Joint Modeling of Response Times with Dynamic Latent Ability in Educational Testing2025
  2. 2Joint Model of a Zero-One Inflated Continuous Item Response Theory Model and a Lognormal Response Time Model for Ability Measurement Using Bounded Continuous Responses and Response Times2026
  3. 3A Unified Framework for Jointly modelling Response Times and Item Position Effects in Computer-Based Learning Assessments2026
  4. 4Bayesian Estimation of a Ramsay-Curve Graded Response Model Using Metropolis–Hastings Sampling Method2026
  5. 5Bayesian Model Assessment Under the Joint IRT and Generalized Odds-Rate Hazards Model for Response and Response Time Data in Computerized Testing2026