ArticleHeliyon2018
Empirical comparison of item response theory models with rater's parameters.
Article in Heliyon, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 38 citations in OpenAlex.
- Linking essay-writing tests using many-facet models and neural automated essay scoring.Behavior research methods · 2024Article
- Harmonizing the CBCL and SDQ ADHD scores by using linear equating, kernel equating, item response theory and machine learning methods.Frontiers in psychology · 2024Article
- Article
- A Bayesian many-facet Rasch model with Markov modeling for rater severity drift.Behavior research methods · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In various assessment contexts including entrance examinations, educational assessments, and personnel appraisal, performance assessment by raters has attracted much attention to measure higher order abilities of examinees. However, a persistent difficulty is that the ability measurement accuracy depends strongly on rater and task characteristics. To resolve this shortcoming, various item response theory (IRT) models that incorporate rater and task characteristic parameters have been proposed. However, because various models with different rater and task parameters exist, it is difficult to understand each model's features. Therefore, this study presents empirical comparisons of IRT models. Specifically, after reviewing and summarizing features of existing models, we compare their performance through simulation and actual data experiments.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.