Psychometric Methods for Diagnostic Assessment and Dimensionality Representation
Bolt, Daniel Marc
This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/82261
Description
Title
Psychometric Methods for Diagnostic Assessment and Dimensionality Representation
Author(s)
Bolt, Daniel Marc
Issue Date
1999
Doctoral Committee Chair(s)
William Stout
Department of Study
Psychology
Discipline
Psychology
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Education, Tests and Measurements
Language
eng
Abstract
A second part of the thesis investigates a new methodology for the representation of multidimensional test structure based on item-pair conditional covariances. The multidimensional ability composite best measured (in terms of information) for an item is sometimes regarded as the measurement direction of the item. We demonstrate how a directional representation of an item can be reconstructed on the basis of the item's pattern of conditional covariances with all of the other items on the test. A proximity measure for item pairs is derived, and circular and spherical scaling techniques are shown to provide a method by which the unique measurement directions of items might be recovered and represented. Several real and simulated data analyses suggest that the approach may be a useful tool for investigating and describing the dimensional structure of tests.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.