Kullback-Leibler information and its applications in multidimensional adaptive testing

This paper first discusses the relationship between Kullback-Leibler information (KL) and Fisher information in the context of multi-dimensional item response theory and is further interpreted for the two-dimensional case, from a geometric perspective. This explication should allow for a better understanding of the various item selection methods in multi-dimensional adaptive tests (MAT) which are based on these two information measures. The KL information index (KI) method is then discussed and two theorems are derived to quantify the relationship between KI and item parameters. Due to the fact that most of the existing item selection algorithms for MAT bear severe computational complexity, which substantially lowers the applicability of MAT, two versions of simplified KL index (SKI), built from the analytical results, are proposed to mimic the behavior of KI, while reducing the overall computational intensity.

Name thesis:degree_name

M.A.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Psychology

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2012

Author dc:creator

• Wang, Chun

Contributors dc:contributor

• Chang, Hua-Hua
• Douglas, Jeffrey A.

• Kullback-Leibler information
• Fisher information
• multi-dimensional adaptive testing

Statement dc:rights

• Copyright 2012 Chun Wang

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/30910

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/30910