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Department of Statistics

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Our department excels at collaborative research between faculty, students and other universities. 

Below lists recent papers (accepted/in press) authored by our tenured/tenure track faculty (shown in bold).

2021 (in progress)
  1. Tang, C., Wang, D., El Barmi, H., and Tebbs, J. (2021). Testing for positive quadrant dependence. American Statistician, in press.
  2. Liu, Y., McMahan, C., Tebbs, J., Gallagher, C., and Bilder, C. (2021). Generalized additive regression for group testing data. Biostatistics, in press.
  3. Bilder, C., Tebbs, J., and McMahan, C. (2021). Informative array testing with multiplex assays. Statistics in Medicine, in press.
  4. Mokalled, S., McMahan, C., Brown, D., Tebbs, J., and Bilder, C. (2021). Incorporating the dilution effect in group testing regression. Statistics in Medicine, in press.
  5. Watson, S., Cooper, K., Liu, P., Gharraee, N., Du, L., Han, S., Peña, E., and others (2021). American Journal of Physiology-Heart and Circulatory Physiology, in press.
  6. Rahman, F. and Peña, E. (2021). Nonparametric Bayes estimation of the reliability function of a coherent system. Journal of Statistical Research, in press.
  7. Huang, X. (2021). Improved wrong-model inference for generalized linear models for binary responses in the presence of link misspecification. Statistical Methods and Applications, in press.
  8. Zhang, H., Huang, X., Han, S., Rezwan, F., Karmaus, W., Arshad, H., and Holloway, J. (2021). Gaussian Bayesian network comparisons with graph ordering unknown. Computational Statistics and Data Analysis, in press.
  9. Huang, X. and Zhang, H. (2021). Corrected score methods for estimating Bayesian networks with error‐prone nodes. Statistics in Medicine, in press.
  10. Huang, X. and Zhang, H. (2021). Tests for differential Gaussian Bayesian networks based on quadratic inference functions.  Computational Statistics and Data Analysis, in press.
  11. Pittman, R., Hitchcock, D., and Grego, J. (2021). Concurrent functional regression to reconstruct river stage data during flood events. Environmental and Ecological Statistics 28, 219-237.
  12. Gu, E., Zhang, J., Lu, W., Wang, L., and Felizzi, F. (2021). Semiparametric estimation of the cure fraction in population-based cancer survival analysis. Statistics in Medicine, in press.
  13. Wang, L. and Wang, L. (2021). EM algorithm for analyzing right-censored data under the semiparametric proportional odds model. Communications in Statistics—Theory and Methods, in press.
  14. Pan, C., Cai, B., and Wang, L. (2021). A Bayesian approach for analyzing partly interval-censored data under the proportional hazards model. Statistical Methods in Medical Research, in press.
  15. Wang, D. and Tang, C. (2021). Testing against uniform stochastic ordering with paired observations. Bernoulli, in press.
  16. Gregory, K., Mammen, E., Wahl, M. (2021). Statistical inference in sparse high-dimensional additive models. Annals of Statistics, in press.
  17. Shin, M. and Liu, J. (2021). Neuronized priors for Bayesian sparse linear regression. Journal of the American Statistical Association, in press.
  18. Bai, R. and Ghosh, M. (2021). On the beta prime prior for scale parameters in high-dimensional Bayesian regression models. Statistica Sinica, in press.
  19. Bai, R., Moran, G., Antonelli, J., Chen, Y., and Boland, M. (2021). Spike-and-slab group lassos for grouped regression and sparse generalized additive models. Journal of the American Statistical Association, in press.
  20. Boland, M., Liu, J., Balocchi, C., Meeker, J., Bai, R., Mowery, D., and Herman, D. (2021). A method to link neighborhood-level covariates to covid-19 infection patterns in Philadelphia using spatial regression. AMIA 2021 Virtual Informatics Summit, accepted.
  1. Joyner, C., McMahan, C., Tebbs, J., and Bilder, C. (2020). From mixed effects modeling to spike and slab variable selection: A Bayesian regression model for group testing data. Biometrics 76, 913-923.
  2. Hou, P., Tebbs, J., Wang, D., McMahan, C., and Bilder, C. (2020). Array testing with multiplex assays. Biostatistics 21, 417-431.
  3. Wang, D., Tang, C., and Tebbs, J. (2020). More powerful goodness-of-fit tests for uniform stochastic ordering. Computational Statistics and Data Analysis 144, 106898.
  4. Bilder, C., Iwen, P., Abdalhamid, B., Tebbs, J., and McMahan, C. (2020). Tests in short supply? Try group testing. Significance 17, 15-16.
  5. Chakrabarti, M., Al-Sammarraie, N., Gebere, M., Bhattacharya, S., Johnson, J., Peña, E., and others (2020). Transforming growth factor Beta3 is required for cardiovascular development. Journal of Cardiovascular Development and Disease 7, 19, doi: 10.3390/jcdd7020019.
  6. Huang, X. and Zhou, H. (2020). Conditional density estimation with covariate measurement error. Electronic Journal of Statistics 14, 970-1023.
  7. Zhou, H. and Huang, X. (2020). Parametric mode regression for bounded responses. Biometrical Journal 61, 1791-1809.
  8. Wang, D., Mou, X., Li, X., and Huang, X. (2020). Local polynomial regression for pooled response data. Journal of Nonparametric Statistics 32, 814-837.
  9. Liu, H., Hitchcock, D., Samadi, S. (2020). Spatio-temporal analysis of flood data from South Carolina. Journal of Statistical Distributions and Applications 7, 11. 
  10. Samadi, S., Pourreza‐Bilondi, M., Wilson, C., and Hitchcock, D. (2020). Bayesian model averaging with fixed and flexible priors: Theory, concepts, and calibration experiments for rainfall‐runoff modeling. Journal of Advances in Modeling Earth Systems, 12, e2019MS001924.
  11. Liu, Q., Hodge, J., Wang, J., Wang, Y., Wang, L., and others (2020). Emodin reduces breast cancer lung metastasis by suppressing macrophage-induced breast cancer cell epithelial mesenchymal transition and cancer stem cell formation. Theranostics 10, 8365-8381.
  12. Mohammadi, E., Gregory, K., Thelwall, M., and Barahmand, N. (2020). Which health and biomedical topics generate the most Facebook interest and the strongest citation relationships? Information Processing and Management 57, 102230.
  13. Baek S., Ho, Y., and Ma, Y. (2020). Using sufficient direction factor model to analyze latent activities associated with breast cancer survival. Biometrics 76, 1340-1350. 
  14. Ma Z., Hanson T., Ho, Y. (2020). Flexible bivariate count data regressions. Statistics in Medicine 39, 3476-3490.
  15. Krizek, B., Blakley, I., Freese, N., Ho, Y., and Loraine A. (2020). The Arabidopsis transcription factor AINTEGUMENTA orchestrates patterning genes and auxin signaling in the establishment of flora growth and form. Plant Journal 103, 752-768.
  16. Yun, J., Shin, M., Jin, I., and Liang, F. (2020). Stochastic approximation Hamiltonian Monte Carlo. Journal of Statistical Computation and Simulation 90, 3135-3156.
  17. Shin, M., Bhattacharya, A., and Johnson, V. (2020). Functional horseshoe prior for subspace shrinkage. Journal of the American Statistical Association 115, 1784-1797.

Challenge the conventional. Create the exceptional. No Limits.