Bayesian modeling of item heterogeneity in dichotomous recognition memory data and prospects for computerized adaptive testing

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Fältnamn	Indikatorer	Metadata
000		04039naa a2200361 4500
001		oai:lup.lub.lu.se:c8831067-e5cc-42b4-abad-9b6632c697db
003		SwePub
008		220324s2022 \| \|\|\|\|\|\|\|\|\|\|\|000 \|\|eng\|
024	7	a https://lup.lub.lu.se/record/c8831067-e5cc-42b4-abad-9b6632c697db2 URI
024	7	a https://doi.org/10.1038/s41598-022-04997-32 DOI
040		a (SwePub)lu
041		a engb eng
042		9 SwePub
072	7	a art2 swepub-publicationtype
072	7	a ref2 swepub-contenttype
100	1	a Güsten, Jeremieu German Center for Neurodegenerative Diseases (DZNE), Bonn,Otto von Guericke University Magdeburg4 aut
245	1 0	a Bayesian modeling of item heterogeneity in dichotomous recognition memory data and prospects for computerized adaptive testing
264		c 2022-01-24
264	1	b Springer Science and Business Media LLC,c 2022
520		a Most current models of recognition memory fail to separately model item and person heterogeneity which makes it difficult to assess ability at the latent construct level and prevents the administration of adaptive tests. Here we propose to employ a General Condorcet Model for Recognition (GCMR) in order to estimate ability, response bias and item difficulty in dichotomous recognition memory tasks. Using a Bayesian modeling framework and MCMC inference, we perform 3 separate validation studies comparing GCMR to the Rasch model from IRT and the 2-High-Threshold (2HT) recognition model. First, two simulations demonstrate that recovery of GCMR ability estimates with varying sparsity and test difficulty is more robust and that estimates improve from the two other models under common test scenarios. Then, using a real dataset, face validity is confirmed by replicating previous findings of general and domain-specific age effects (Güsten et al. in Cortex 137:138–148, https://doi.org/10.1016/j.cortex.2020.12.017, 2021). Using cross-validation we show better out-of-sample prediction for the GCMR as compared to Rasch and 2HT model. In addition, we present a hierarchical extension of the model that is able to estimate age- and domain-specific effects directly, without recurring to a two-stage procedure. Finally, an adaptive test using the GCMR is simulated, showing that the test length necessary to obtain reliable ability estimates can be significantly reduced compared to a non-adaptive procedure. The GCMR allows to model trial-by-trial performance and to increase the efficiency and reliability of recognition memory assessments.
650	7	a NATURVETENSKAPx Data- och informationsvetenskapx Bioinformatik0 (SwePub)102032 hsv//swe
650	7	a NATURAL SCIENCESx Computer and Information Sciencesx Bioinformatics0 (SwePub)102032 hsv//eng
650	7	a MEDICIN OCH HÄLSOVETENSKAPx Medicinsk bioteknologix Biomedicinsk laboratorievetenskap/teknologi0 (SwePub)304022 hsv//swe
650	7	a MEDICAL AND HEALTH SCIENCESx Medical Biotechnologyx Biomedical Laboratory Science/Technology0 (SwePub)304022 hsv//eng
700	1	a Berron, Davidu Lund University,Lunds universitet,Klinisk minnesforskning,Forskargrupper vid Lunds universitet,Clinical Memory Research,Lund University Research Groups,German Center for Neurodegenerative Diseases (DZNE), Bonn4 aut0 (Swepub:lu)da1401be
700	1	a Düzel, Emrahu German Center for Neurodegenerative Diseases (DZNE), Bonn,Otto von Guericke University Magdeburg4 aut
700	1	a Ziegler, Gabrielu Otto von Guericke University Magdeburg,German Center for Neurodegenerative Diseases (DZNE), Bonn4 aut
710	2	a German Center for Neurodegenerative Diseases (DZNE), Bonnb Otto von Guericke University Magdeburg4 org
773	0	t Scientific Reportsd : Springer Science and Business Media LLCg 12:1q 12:1x 2045-2322
856	4	u http://dx.doi.org/10.1038/s41598-022-04997-3x freey FULLTEXT
856	4	u https://www.nature.com/articles/s41598-022-04997-3.pdf
856	4 8	u https://lup.lub.lu.se/record/c8831067-e5cc-42b4-abad-9b6632c697db
856	4 8	u https://doi.org/10.1038/s41598-022-04997-3

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Av författaren/redakt...: Güsten, Jeremie; Berron, David; Düzel, Emrah; Ziegler, Gabriel

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