Files in this item

FilesDescriptionFormat

application/pdf

application/pdf3153470.pdf (3MB)Restricted to U of Illinois
(no description provided)PDF

Description

Title:Computerized Adaptive Testing and Equating Methods With Nonparametric IRT Models
Author(s):Xu, Xueli
Doctoral Committee Chair(s):Douglas, Jeffrey
Department / Program:Statistics
Discipline:Statistics
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Statistics
Abstract:The flexible forms of nonparametric IRT models make test equating more challenging. Though linear equating under parametric IRT models is obvious and appropriate, it might not be appropriate for nonparametric models. Two approaches are proposed for test equating and examined through simulation as well as with real data analysis. The simulation studies show that both approaches are able to recover the true equating functions with tolerable error. The real data analysis shows that these two approaches lead to similar equating functions.
Issue Date:2004
Type:Text
Language:English
Description:77 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2004.
URI:http://hdl.handle.net/2142/87399
Other Identifier(s):(MiAaPQ)AAI3153470
Date Available in IDEALS:2015-09-28
Date Deposited:2004


This item appears in the following Collection(s)

Item Statistics