Evidence map›Paper›PMID 34725802›Full record

ArticleBehavior research methods2022

A new item response theory model for rater centrality using a hierarchical rater model approach.

Xue-Lan Qiu, Ming Ming Chiu, Wen-Chung Wang, Po-Hsi Chen

Abstract read
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Article in Behavior research methods, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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.

2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Xue-Lan QiuFaculty of Education, The University of Hong Kong, Hong Kong, China. xlqiu@hku.hk.
Ming Ming ChiuDepartment of Special Education and Counselling, The Education University of Hong Kong, Hong Kong, China.
Wen-Chung WangDepartment of Psychology, The Education University of Hong Kong, Hong Kong, China.
Po-Hsi ChenDepartment of Educational Psychology and Counselling, Institute for Research Excellence in Learning Sciences, National Taiwan Normal University, Taipei City, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rater centrality, in which raters overuse middle scores for rating, is a common rater error which can affect test scores and subsequent decisions. Past studies on rater errors have focused on rater severity and inconsistency, neglecting rater centrality. This study proposes a new model within the hierarchical rater model framework to explicitly specify and directly estimate rater centrality in addition to rater severity and inconsistency. Simulations were conducted using the freeware JAGS to evaluate the parameter recovery of the new model and the consequences of ignoring rater centrality. The results revealed that the model had good parameter recovery with small bias, low root mean square errors, and high test score reliability, especially when a fully crossed linking design was used. Ignoring centrality yielded poor item difficulty estimates, person ability estimates, rater errors estimates, and underestimated reliability. We also showcase how the new model can be used, using an empirical example involving English essays in the Advanced Placement exam.

Indexed as

Models, StatisticalResearch PersonnelBiasHumansReproducibility of ResultsCentrality effectHierarchical rater modelItem response theoryRater errors

Identifiers

PMID34725802

What OpenQuestion holds

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Registered trials

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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.