ERIC Number: EJ1124703
Record Type: Journal
Publication Date: 2016-May
Pages: 14
Abstractor: As Provided
ISBN: N/A
ISSN: EISSN-2330-8516
EISSN: N/A
Applications of Multidimensional Item Response Theory Models with Covariates to Longitudinal Test Data. Research Report. ETS RR-16-21
Fu, Jianbin
ETS Research Report Series, May 2016
The multidimensional item response theory (MIRT) models with covariates proposed by Haberman and implemented in the "mirt" program provide a flexible way to analyze data based on item response theory. In this report, we discuss applications of the MIRT models with covariates to longitudinal test data to measure skill differences at the individual and group levels. In particular, we describe the differential item functioning procedure to identify common items with item drift across test occasions, and model selection and evaluation based on model comparison, fit statistics, and skill estimates. A real dataset on algebra tests is used to demonstrate the applications.
Descriptors: Item Response Theory, Longitudinal Studies, Test Bias, Goodness of Fit, Mathematics Tests, Algebra, Data Analysis, Models, National Competency Tests, Grade 8, Correlation
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Publication Type: Journal Articles; Reports - Research
Education Level: Grade 8; Junior High Schools; Middle Schools; Elementary Education; Secondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Assessments and Surveys: National Assessment of Educational Progress
Grant or Contract Numbers: N/A