Modeling Multiple Item Context Effects With Generalized Linear Mixed Models

Item context effects refer to the impact of features of a test on an examinee's item responses. These effects cannot be explained by the abilities measured by the test. Investigations typically focus on only a single type of item context effects, such as item position effects, or mode effects,...

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Vydáno v:	Frontiers in psychology Ročník 10; s. 248
Hlavní autoři:	Rose, Norman, Nagy, Gabriel, Nagengast, Benjamin, Frey, Andreas, Becker, Michael
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Switzerland Frontiers Media S.A 25.02.2019
Témata:	domain order effects generalized linear mixed models item context effects item position effects multidimensional item response theory Psychology item position effects multidimensional item response theory generalized linear mixed models domain order effects item context effects
ISSN:	1664-1078, 1664-1078
On-line přístup:	Získat plný text
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Popis
Shrnutí:	Item context effects refer to the impact of features of a test on an examinee's item responses. These effects cannot be explained by the abilities measured by the test. Investigations typically focus on only a single type of item context effects, such as item position effects, or mode effects, thereby ignoring the fact that different item context effects might operate simultaneously. In this study, two different types of context effects were modeled simultaneously drawing on data from an item calibration study of a multidimensional computerized test ( = 1,632) assessing student competencies in mathematics, science, and reading. We present a generalized linear mixed model (GLMM) parameterization of the multidimensional Rasch model including (distinguishing between and ), , and the interactions between them. Results show that both types of context effects played a role, and that the moderating effect of domain orders was very strong. The findings have direct consequences for planning and applying mixed domain assessment designs.
Bibliografie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 This article was submitted to Quantitative Psychology and Measurement, a section of the journal Frontiers in Psychology Edited by: Holmes Finch, Ball State University, United States Reviewed by: Anthony D. Albano, University of Nebraska System, United States; Maria Anna Donati, Università Degli Studi di Firenze, Italy
ISSN:	1664-1078 1664-1078
DOI:	10.3389/fpsyg.2019.00248