Hongwei (Patrick) Yang, Ph.D, University of Tennessee, 2008. Assistant Professor
Dr. Yang (vita in PDF) joined the faculty in 2008. He is a quantitative methodologist whose research interests revolve around the following areas:
Latent variable modeling Various issues in latent variable modeling which includes structural equation models (SEM), latent trait models (IRT), etc. Particularly interested in model evaluation and selection using entropy-based information criteria in those latent variable modeling problems using multilevel, mixture, or a combination of multilevel and mixture structures
Mixed effects modeling Various issues in mixed effects models including hierarchical linear models (HLM): Model estimation, evaluation, and selection, etc. Issues around longitudinal data modeling using mixed-effects models (and latent growth curve models)
Statistical data mining and text mining The use of data mining techniques in educational research for description and prediction. Particularly interested in decision tree models and neural network models for predicting and evaluating educational outcomes. Also interested in textual data analysis in discovering the underlying themes or concepts that are contained in large document collections
Statistics education Helping and motivating students to learn and use statistics, particularly with the use of modern computer technology
R programming Using the free R language in statistical and psychometric simulation studies and for instructional purposes.