University of Illinois Urbana-Champaign

Likelihood estimation for jointly analyzing item responses and response times

Kang, Hyeon-Ah

Content Files
KANG-DISSERTATION-2016.pdf

Permalink

https://hdl.handle.net/2142/92803

Description

Title
Likelihood estimation for jointly analyzing item responses and response times
Author(s)
Kang, Hyeon-Ah
Issue Date
2016-07-12
Director of Research (if dissertation) or Advisor (if thesis)
Chang, Hua-Hua
Doctoral Committee Chair(s)
Chang, Hua-Hua
Committee Member(s)
  • Anderson, Carolyn J.
  • Culpepper, Steven A.
  • Douglas, Jeffrey A.
  • Koehn, Hans-Friedrich
  • Zhang, Jinming
Department of Study
Educational Psychology
Discipline
Educational Psychology
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Date of Ingest
2016-11-10T17:54:52Z
Keyword(s)
  • response time
  • item response theory
Abstract
Response time has become increasingly important for analyzing the relationship between the proficiency and speed of an examinee. In this thesis, statistical estimation procedures are presented for jointly modeling responses and response times in educational and psychological testing. The models under consideration include the three-parameter logistic response model, the lognormal response time model, and the proportional hazards latent trait model. The individual models are conjoined within the hierarchical framework so that parameters in the respective models can be characterized under a unified scheme. The thesis presents estimation methods for each of the combinations of the response and response time models by maximizing the likelihood functions. A series of simulation studies verify that the estimation methods perform appropriately, and the parameters are robustly estimated. The likelihood-based approach provides a practical and efficient alternative to Bayesian estimation procedures, which often comes with high computational intensity and dependence on priors.
Graduation Semester
2016-08
Type of Resource
text
Permalink
http://hdl.handle.net/2142/92803
Copyright and License Information
2016 by Hyeon-Ah Kang. All rights reserved.

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