Linking of Rasch-Scaled Tests: Consequences of Limited Item Pools and Model Misfit.

Rasch model anchor- items design item response theory limited item pools linking methods model misfit

Journal

Frontiers in psychology
ISSN: 1664-1078
Titre abrégé: Front Psychol
Pays: Switzerland
ID NLM: 101550902

Informations de publication

Date de publication:
2021
Historique:
received: 26 11 2020
accepted: 14 06 2021
entrez: 23 7 2021
pubmed: 24 7 2021
medline: 24 7 2021
Statut: epublish

Résumé

In the context of item response theory (IRT), linking the scales of two measurement points is a prerequisite to examine a change in competence over time. In educational large-scale assessments, non-identical test forms sharing a number of anchor-items are frequently scaled and linked using two- or three-parametric item response models. However, if item pools are limited and/or sample sizes are small to medium, the sparser Rasch model is a suitable alternative regarding the precision of parameter estimation. As the Rasch model implies stricter assumptions about the response process, a violation of these assumptions may manifest as model misfit in form of item discrimination parameters empirically deviating from their fixed value of one. The present simulation study investigated the performance of four IRT linking methods-fixed parameter calibration, mean/mean linking, weighted mean/mean linking, and concurrent calibration-applied to Rasch-scaled data with a small item pool. Moreover, the number of anchor items required in the absence/presence of moderate model misfit was investigated in small to medium sample sizes. Effects on the link outcome were operationalized as bias, relative bias, and root mean square error of the estimated sample mean and variance of the latent variable. In the light of this limited context, concurrent calibration had substantial convergence issues, while the other methods resulted in an overall satisfying and similar parameter recovery-even in the presence of moderate model misfit. Our findings suggest that in case of model misfit, the share of anchor items should exceed 20% as is currently proposed in the literature. Future studies should further investigate the effects of anchor item composition regarding unbalanced model misfit.

Identifiants

pubmed: 34295279
doi: 10.3389/fpsyg.2021.633896
pmc: PMC8289883
doi:

Types de publication

Journal Article

Langues

eng

Pagination

633896

Informations de copyright

Copyright © 2021 Fischer, Rohm, Carstensen and Gnambs.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Références

Psychometrika. 2016 Sep;81(3):650-73
pubmed: 26155754
Front Psychol. 2017 Apr 04;8:484
pubmed: 28421011
J Appl Meas. 2018;19(3):216-228
pubmed: 30169331

Auteurs

Luise Fischer (L)

Leibniz Institute for Educational Trajectories, Bamberg, Germany.
Psychological Methods of Educational Research, University of Bamberg, Bamberg, Germany.

Theresa Rohm (T)

Leibniz Institute for Educational Trajectories, Bamberg, Germany.
Psychological Methods of Educational Research, University of Bamberg, Bamberg, Germany.

Claus H Carstensen (CH)

Psychological Methods of Educational Research, University of Bamberg, Bamberg, Germany.

Timo Gnambs (T)

Leibniz Institute for Educational Trajectories, Bamberg, Germany.

Classifications MeSH