Evidence map›Paper›PMID 32803390›Full record

ArticlePsychometrika2020

A Restricted Four-Parameter IRT Model: The Dyad Four-Parameter Normal Ogive (Dyad-4PNO) Model.

Justin L Kern, Steven Andrew Culpepper

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Article in Psychometrika, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
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1 · What the graph read from it

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.

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Justin L KernDepartment of Educational Psychology, University of Illinois at Urbana-Champaign, 725 South Wright Street, Champaign, IL, 61820, USA.ORCID 0000-0002-4772-2241
Steven Andrew CulpepperDepartment of Statistics, University of Illinois at Urbana-Champaign, 725 South Wright Street, Champaign, IL, 61820, USA. sculpepp@illinois.edu.ORCID 0000-0003-4226-6176

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, there has been a renewed interest in the four-parameter item response theory model as a way to capture guessing and slipping behaviors in responses. Research has shown, however, that the nested three-parameter model suffers from issues of unidentifiability (San Martín et al. in Psychometrika 80:450-467, 2015), which places concern on the identifiability of the four-parameter model. Borrowing from recent advances in the identification of cognitive diagnostic models, in particular, the DINA model (Gu and Xu in Stat Sin https://doi.org/10.5705/ss.202018.0420 , 2019), a new model is proposed with restrictions inspired by this new literature to help with the identification issue. Specifically, we show conditions under which the four-parameter model is strictly and generically identified. These conditions inform the presentation of a new exploratory model, which we call the dyad four-parameter normal ogive (Dyad-4PNO) model. This model is developed by placing a hierarchical structure on the DINA model and imposing equality constraints on a priori unknown dyads of items. We present a Bayesian formulation of this model, and show that model parameters can be accurately recovered. Finally, we apply the model to a real dataset.

Indexed as

Models, StatisticalPsychometricsBayes TheoremBayesian statisticsfour-parameter modelhierarchical DINA modelidentificationslipping

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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.