University of Illinois Urbana-Champaign

New nonparametric statistical procedures for analyzing bias/DIF and dimensionality in item response data

Li, Hsin-Hung

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Description

Title
New nonparametric statistical procedures for analyzing bias/DIF and dimensionality in item response data
Author(s)
Li, Hsin-Hung
Issue Date
1995
Doctoral Committee Chair(s)
Stout, William F.
Department of Study
Statistics
Discipline
Statistics
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
  • Education, Tests and Measurements
  • Statistics
  • Psychology, Psychometrics
Language
eng
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.
Type of Resource
text
Permalink
http://hdl.handle.net/2142/22859
Copyright and License Information
Copyright 1995 Li, Hsin-Hung

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