A New Multiprocess IRT Model with Ideal Points for Likert-Type Items

Autor/inn/en	Jin, Kuan-Yu; Wu, Yi-Jhen; Chen, Hui-Fang
Titel	A New Multiprocess IRT Model with Ideal Points for Likert-Type Items
Quelle	In: Journal of Educational and Behavioral Statistics, 47 (2022) 3, S.297-321 (25 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Jin, Kuan-Yu) ORCID (Wu, Yi-Jhen)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1076-9986
DOI	10.3102/10769986211057160
Schlagwörter	Likert Scales; Item Response Theory; Surveys; Responses; Item Analysis; Models; Decision Making; Psychological Studies; Bayesian Statistics; Welfare Services; Public Policy; Foreign Countries; Social Life; Sexuality; Health Behavior; Social Attitudes; Europe; Czech Republic + Suchen Sie Ihr Suchwort? Likert-Skala; Item-Response-Theorie; Survey; Umfrage; Befragung; Itemanalyse; Analogiemodell; Decision-making; Entscheidungsfindung; Fürsorgeeinrichtung; Öffentliche Ordnung; Ausland; Soziales Leben; Sexualität; Health behaviour; Gesundheitsverhalten; Social attidude; Soziale Einstellung; Europa; Tschechische Republik
Abstract	For surveys of complex issues that entail multiple steps, multiple reference points, and nongradient attributes (e.g., social inequality), this study proposes a new multiprocess model that integrates ideal-point and dominance approaches into a treelike structure (IDtree). In the IDtree, an ideal-point approach describes an individual's attitude and then a dominance approach describes their tendency for using extreme response categories. Evaluation of IDtree performance via two empirical data sets showed that the IDtree fit these data better than other models. Furthermore, simulation studies showed a satisfactory parameter recovery of the IDtree. Thus, the IDtree model sheds light on the response processes of a multistage structure. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01