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Applied Psychological Measurement >
Volume 20, 1996 >
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| Title: | Conditional covariance-based nonparametric multidimensionality assessment |
| Authors: | Stout, William
Habing, Brian
Douglas, Jeff
Kim, Hae Rim
Roussos, Louis
Zhang, Jinming |
| Issue Date: | 1996 |
| Citation: | Stout, William, Habing, Brian, Douglas, Jeff & Kim, Hae Rim. (1996). Conditional covariance-based nonparametric multidimensionality assessment. Applied Psychological Measurement, 20, 331-354. doi:10.1177/014662169602000403 |
| Abstract: | According to the weak local independence approach
to defining dimensionality, the fundamental quantities
for determining a test’s dimensional structure are the covariances
of item-pair responses conditioned on examinee
trait level. This paper describes three
dimensionality assessment
procedures-HCA/CCPROX,
DIMTEST, and DETECT-that use estimates of these conditional
covariances. All three procedures are nonparametric
; that is, they do not depend on the functional
form of the item response functions. These procedures
are applied to a dimensionality study of the LSAT, which
illustrates the capacity of the approaches to assess the
lack of unidimensionality, identify groups of items
manifesting approximate simple structure, determine the
number of dominant dimensions, and measure the
amount of multidimensionality. Index terms: approximate
simple structure, conditional covariance, DETECT,
dimensionality, DIMTEST, HCA/CCPROX,
hierarchical cluster analysis, IRT, LSAT, local independence, multidimensionality, simple structure. |
| Permanent URL: | http://purl.umn.edu/119466 |
| Appears in Collections: | Volume 20, 1996
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| v20n4p331.pdf | | 1753Kb | PDF | View/Open |
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