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Modeling item position effects with a Bayesian item response model applied to PISA 2009–2015 data
Trendtel, M., Robitzsch, A.

Modeling item position effects with a Bayesian item response model applied to PISA 2009–2015 data

Psychological Test and Assessment Modeling, 60(2), 241-263.

Previous studies have repeatedly  demonstrated the existence of item position effects in large-scale  assessments. Usually, items are answered correctly more often whenadministered 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 StudentAssessment (PISA) for six countries.