Open Access“THIN” VERSUS “THICK” MATCHING IN THE MANTEL‐HAENSZEL PROCEDURE FOR DETECTING DIF
Author(s) -
Donoghue John R.,
Allen Nancy L.
Publication year - 1992
Publication title -
ets research report series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.235
H-Index - 5
ISSN - 2330-8516
DOI - 10.1002/j.2333-8504.1992.tb01507.x
Subject(s) - matching (statistics) , statistics , pooling , statistic , mathematics , test statistic , statistical hypothesis testing , artificial intelligence , computer science
This Monte Carlo study examined strategies for forming the matching variable for the Mantel‐Haenszel DIF procedure; “thin” matching on total test score was compared to forms of “thick” matching, pooling levels of the matching variable. Data were generated using a three‐parameter item response theory model with common guessing parameter. Number of subjects and test length were manipulated, as were the difficulty, discrimination, and presence/absence of DIF in the studied item. Outcome measures were the transformed log‐odds Δ̂ MH , its standard error, and the MH chi‐square statistic. For short tests (5 or 10 items), thin matching yielded very poor results, with a tendency to falsely identify items as possessing DIF against the reference group. The best methods of thick matching yielded outcome measure values closer to the expected value for non‐DIF items, and a larger value than thin matching when the studied item possessed DIF. Intermediate length tests yielded similar results for thin matching and the best methods of thick matching. The method of thick matching that performed best depended upon the measure used to detect DIF. Both difficulty and discrimination of the studied item were found to have a strong effect on the value of Δ MH .