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Comparing Multiunidimensional and Unidimensional Item Response Theory Models

Southern Illinois University Carbondale, ysheng{at}siu.edu

Christopher K. Wikle

University of Missouri-Columbia

For tests consisting of multiple subtests, unidimensional item response theory (IRT) models apply when the subtests are known to measure a common underlying ability. However, in many instances, due to the lack of a satisfactory index for assessing the dimensionality assumption, the test structure is not clear. A more general IRT model, the multiunidimensional model, is more flexible and efficient in various test situations. This article compares these two classes of normal ogive two-parameter models and shows that the multiunidimensional model offers a better way to represent test situations not realized in unidimensional models.

Key Words: item response theory • unidimensional model • multiunidimensional model • Markov chain Monte Carlo • Bayesian model choice

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This version was published on December 1, 2007

Educational and Psychological Measurement, Vol. 67, No. 6, 899-919 (2007)
DOI: 10.1177/0013164406296977


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