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Using Dimensionality‐Based DIF Analyses to Identify and Interpret Constructs That Elicit Group Differences
Author(s) -
Gierl Mark J.
Publication year - 2005
Publication title -
educational measurement: issues and practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.158
H-Index - 52
eISSN - 1745-3992
pISSN - 0731-1745
DOI - 10.1111/j.1745-3992.2005.00002.x
Subject(s) - matching (statistics) , psychology , selection (genetic algorithm) , curse of dimensionality , contrast (vision) , cognitive psychology , test (biology) , social psychology , computer science , statistics , artificial intelligence , mathematics , paleontology , biology
In this paper I describe and illustrate the Roussos‐Stout (1996) multidimensionality‐based DIF analysis paradigm, with emphasis on its implication for the selection of a matching and studied subtest for DIF analyses. Standard DIF practice encourages an exploratory search for matching subtest items based on purely statistical criteria, such as a failure to display DIF. By contrast, the multidimensional DIF paradigm emphasizes a substantively‐informed selection of items for both the matching and studied subtest based on the dimensions suspected of underlying the test data. Using two examples, I demonstrate that these two approaches lead to different interpretations about the occurrence of DIF in a test. It is argued that selecting a matching and studied subtest, as identified using the DIF analysis paradigm, can lead to a more informed understanding of why DIF occurs.