Modeling Item Position Effects with a Bayesian Item Response Model Applied to PISA 2009-2015 Data.

Autor/inn/en	Trendtel, Matthias; Robitzsch, Alexander
Titel	Modeling Item Position Effects with a Bayesian Item Response Model Applied to PISA 2009-2015 Data.
Quelle	In: Psychological test and assessment modeling, 60 (2018) 2, S. 241-263 PDF als Volltext kostenfreie Datei Link als defekt meldenVerfügbarkeit
Beigaben	Literaturangaben
Sprache	englisch
Dokumenttyp	online; gedruckt; Zeitschriftenaufsatz
ISSN	2190-0493; 2190-0507
Schlagwörter	Clusteranalyse; Testkonstruktion; Itemanalyse; Schülerleistung; Datenauswertung; Lesekompetenz; Lesen; Cluster; Bayes-Statistik; Leistungsmessung; Modellierung; PISA (Programme for International Student Assessment)
Abstract	Previous studies have repeatedly demonstrated the existence of item position effects in large-scale assessments. Usually, items are answered correctly more often when administered at the beginning of a test compared to at the end of a test. In this article, the aspects of item position effects that are investigated are their pattern, whether they remain stable over time, and whether they are affected by changes in the test administration mode. For this purpose, a Bayesian item response model for modeling item position effects is proposed. This model allows for nonlinear position effects on the item side and linear individual differences on the person side. A full Bayesian estimation procedure is proposed as well as its extension to data collected from stratified clustered samples. The model was applied to the reading data collected in the 2009, 2012, and 2015 cycles of the Programme for International Student Assessment (PISA) for six countries. (Orig.).
Erfasst von	DIPF \| Leibniz-Institut für Bildungsforschung und Bildungsinformation, Frankfurt am Main
Update	2021/2