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Detecting Multidimensionality Due to Curricular Differences
Author(s) -
DeMars Christine E.
Publication year - 2003
Publication title -
journal of educational measurement
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.917
H-Index - 47
eISSN - 1745-3984
pISSN - 0022-0655
DOI - 10.1111/j.1745-3984.2003.tb01095.x
Subject(s) - trait , contrast (vision) , correlation , item response theory , test (biology) , psychology , econometrics , statistics , mathematics , computer science , psychometrics , biology , artificial intelligence , ecology , geometry , programming language
Data were generated to simulate multidimensionality resulting from including two or four subtopics on a test. Each item was dependent on an ability trait due to instruction and learning, which was the same across all items, as well as an ability trait unique to the subtopic of the test (such as biology on a general science test). The eigenvalues of the item correlation matrix and Yen's Q 3 were not greatly influenced by multidimensionality under conditions where the responses of a large proportion of students shared the influence of common instruction across subtopics. In contrast, Stout's T procedure was effective at detecting this type of multidimensionality, unless the subtopic abilities were correlated.