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ERIC Number: EJ1281707
Record Type: Journal
Publication Date: 2021-Feb
Pages: 24
Abstractor: As Provided
ISSN: ISSN-0013-1644
A Mixture IRTree Model for Extreme Response Style: Accounting for Response Process Uncertainty
Kim, Nana; Bolt, Daniel M.
Educational and Psychological Measurement, v81 n1 p131-154 Feb 2021
This paper presents a mixture item response tree (IRTree) model for extreme response style. Unlike traditional applications of single IRTree models, a mixture approach provides a way of representing the mixture of respondents following different underlying response processes (between individuals), as well as the uncertainty present at the individual level (within an individual). Simulation analyses reveal the potential of the mixture approach in identifying subgroups of respondents exhibiting response behavior reflective of different underlying response processes. Application to real data from the Students Like Learning Mathematics (SLM) scale of Trends in International Mathematics and Science Study (TIMSS) 2015 demonstrates the superior comparative fit of the mixture representation, as well as the consequences of applying the mixture on the estimation of content and response style traits. We argue that methodology applied to investigate response styles should attend to the inherent uncertainty of response style influence due to the likely influence of both response styles and the content trait on the selection of extreme response categories.
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Publication Type: Journal Articles; Reports - Evaluative
Education Level: Elementary Secondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Assessments and Surveys: Trends in International Mathematics and Science Study