Computerized Adaptive Testing and Equating Methods With Nonparametric IRT Models

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.

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

2015

Author dc:creator

• Xu, Xueli

Contributors dc:contributor

• Douglas, Jeffrey

• Statistics

Language dc:language

eng

Identifier

(MiAaPQ)AAI3153470

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/87399