Sample Size Requirements for Parameter Recovery in the 4-Parameter Logistic Model

Autor/in	Cuhadar, Ismail
Titel	Sample Size Requirements for Parameter Recovery in the 4-Parameter Logistic Model
Quelle	In: Measurement: Interdisciplinary Research and Perspectives, 20 (2022) 2, S.57-72 (16 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Cuhadar, Ismail)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1536-6367
DOI	10.1080/15366367.2021.1934805
Schlagwörter	Sample Size; Item Response Theory; Test Items; Mathematical Models; Computation; Accuracy; Discriminant Analysis + Suchen Sie Ihr Suchwort? Item-Response-Theorie; Test content; Testaufgabe; Mathematical model; Mathematisches Modell; Diskriminanzanalyse
Abstract	In practice, some test items may display misfit at the upper-asymptote of item characteristic curve due to distraction, anxiety, or carelessness by the test takers (i.e., the slipping effect). The conventional item response theory (IRT) models do not take the slipping effect into consideration, which may violate the model fit assumption in IRT. The 4-parameter logistic model (4PLM) includes a parameter for the misfit at the upper-asymptote. Although the 4PLM took more attention by researchers in recent years, there are a few studies on the sample size requirements for the 4PLM in the literature. The current study investigated the sample size requirements for the parameter recovery in the 4PLM with a systematic simulation study design. Results indicated that the item parameters in the 4PLM can be estimated accurately when the sample size is at least 4000, and the person parameters, excluding the extreme ends of the ability scale, can be estimated accurately for the conditions with a sample size of at least 750. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01