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February 6, 2026British Journal of Mathematical and Statistical PsychologyOpen Access

Latent Poisson count models for action count data from technology‐enhanced assessments

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Authors

GAGregory ArbetThe University of Texas at AustinHKHyeon‐Ah Kang

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Implication

Demonstrates how refined Poisson models analyze action counts in innovative item formats, suggesting practical assessment applications.

Key Points

  • The aim is to develop flexible models to analyze action counts from technology-enhanced assessments while accounting for item type effects.
  • Introduced a refinement scheme to model item-type influences on action counts.
  • Applied multifaceted parameterization in existing Rasch and Conway–Maxwell–Poisson models.
  • Utilized Stan for inference procedures and accuracy validation using simulated data.
  • The proposed model effectively recovers underlying parameters from simulated data.
  • Empirical application revealed distinct item-type effects in action counts.
  • Practical considerations for using Poisson models in count data analysis were discussed.

Cite This Study

Arbet et al. (2026) studied this question.

synapsesocial.com/papers/698585678f7c464f23008b65https://doi.org/10.1111/bmsp.70036
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