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|Title:||New nonparametric statistical procedures for analyzing bias/DIF and dimensionality in item response data|
|Doctoral Committee Chair(s):||Stout, William F.|
|Department / Program:||Statistics|
|Degree Granting Institution:||University of Illinois at Urbana-Champaign|
|Subject(s):||Education, Tests and Measurements
|Abstract:||Unidimensionality is one of the most important assumptions required by much of the currently used item response theory (IRT) methodologies. In the first part of this thesis, a further and non-trivial practical refinement of DIMTEST(Stout, 1987; Nandakumar & Stout, 1993) is made to assess latent trait unidimensionality for mixed dichotomous and polytomous items. The modification is referred to Poly-DIMTEST. The new test statistic for polytomous item scoring was carefully developed and defended with an appropriate asymptotic theory. A simulation study then was carried out to investigate the performance of Poly-DIMTEST. The results demonstrate that Poly-DIMTEST has good Type I error as well as good power. We conclude that the Poly-DIMTEST procedure shows promise as a useful tool in assessing unidimensionality for mixed dichotomous and polytomous test data.
The purpose of the second part of this thesis is to present a hypothesis testing and estimation procedure, Crossing SIBTEST, for detecting crossing DIF. Crossing DIF exists when the difference in the probabilities of a correct answer for the two examinee groups changes signs as ability level is varied. In item response theory terms, crossing DIF is indicated by two crossing item characteristic curves. Our new procedure, denoted as Crossing SIBTEST, first estimates the matching subtest score at which crossing occurs using least squares regression analysis. A Crossing SIBTEST statistic then is used to test the hypothesis of crossing DIF. The performance of Crossing SIBTEST is evaluated in this study.
|Rights Information:||Copyright 1995 Li, Hsin-Hung|
|Date Available in IDEALS:||2011-05-07|
|Identifier in Online Catalog:||AAI9543649|