Professor and Chair
Address: Office: 458 Mathematical Sciences Building
Department of Mathematics and Statistics
Bowling Green State University
Bowling Green, OH 43403-0206
- Mixed Models and Generalized Linear Models
- Model Selection and Modeling Diagnostics
- Multiple Comparison Procedures
- Bayesian Analysis
- Ph.D., Statistics, University of Missouri, Columbia, 2005
Xiong, J. and Shang, J. (2019). A penalized approach to mixed model selection via crossvalidation. Communications in Statistics-Theory and Methods. https://doi.org/10.1080/03610926.2019.1669806.
Switlyk, V. and Shang, J. (2019). Comparison of models for the prediction of the stock price. Journal of Mathematics and Statistics, 15, 233-249.
Pan, J. and Shang, J. (2018). A simultaneous variable selection methodology for linear mixed models. Journal of Statistical Computation and Simulation, 88(17), 3323-3337.
Pan, J. and Shang, J. (2018). Adaptive Lasso for linear mixed model selection via profile loglikelihood. Communications in Statistics-Theory and Methods, 47(8), 1882-1900.
Pan, J. and Shang, J. (2017). Prediction of colon cancer expense via adaptive penalized mixed model selection. Mathematica in Engineering, Science and Aerospace (MESA), 8(2), 253-264.
Shang, J. (2016). A diagnostic of influential cases based on the Information Complexity Criteria in generalized linear mixed models. Communications in Statistics-Theory and Methods, 45 (13), 3751-3760.
Wenren, C., Shang, J. and Pan, J. (2016). Marginal conceptual predictive statistic for mixed model selection. Open Journal of Statistics, 6, 239-253.
Wenren, C. and Shang, J. (2016). Conditional conceptual predictive statistic for mixed model selection. Journal of Applied Statistics, 43 (4), 585-603.
Luo, J. and Shang, J. (2016). Exploratory data analysis on the unemployment rates in USA. Advances and Applications in Statistics, 48 (4), 303-316.