Likelihood estimation for jointly analyzing item responses and response times

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