Applications of computational statistics in cognitive diagnosis and IRT modeling

The identifiability and estimability of the parameters for the Unified Cognitive/IRT Model are studies. A calibration procedure for the Unified Model is then proposed. This procedure uses the marginal maximum likelihood estimation approach and utilizes the EM algorithm. It differs from other calibration procedures for IRT models such as BILOG in that we use Genetic Algorithm in the maximization (M) Step of the EM algorithm. Procedures for classifying examinees are also proposed. A simulation study shows that our calibration procedure works remarkably well for a wide variety of model settings.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Statistics

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2011

Author dc:creator

• Jiang, Hai

Contributors dc:contributor

• Stout, William F.

• Statistics
• Psychology, Psychometrics

Statement dc:rights

• Copyright 1996 Jiang, Hai

Language dc:language

eng

Identifier

9780591199130
AAI9712323
(UMI)AAI9712323

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/20176