Theses Doctoral

Three Contributions to Latent Variable Modeling

Liu, Xiang

The dissertation includes three papers that address some theoretical and technical issues of latent variable models. The first paper extends the uniformly most powerful test approach for testing person parameter in IRT to the two-parameter logistic models. In addition, an efficient branch-and-bound algorithm for computing the exact p-value is proposed. The second paper proposes a reparameterization of the log-linear CDM model. A Gibbs sampler is developed for posterior computation. The third paper proposes an ordered latent class model with infinite classes using a stochastic process prior. Furthermore, a nonparametric IRT application is also discussed.


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More About This Work

Academic Units
Measurement and Evaluation
Thesis Advisors
DeCarlo, Lawrence
Ph.D., Columbia University
Published Here
December 10, 2018