Chong Wang

PhD

Professor
Vet Diagnostic & Production Animal Medicine
Veterinary Preventive Medicine Graduate Programs
chwang@iastate.edu
515-294-3836
2239 Lloyd
ISU Directory Link

General

CV

Education & Certifications

PhD, Statistics, minor in Epidemiology, Cornell University, 2006

Teaching

VDPAM 527 - Applied Statistical Methods in Population Studies
STAT 587 - Statistical Methods for Research Workers
STAT 565 - Methods in Biostatistics and Epidemiology

Research Focus & Interests

Statistics, Biostatistics, Epidemiology, Diagnostic Test Evaluation, Bioinformatics, Animal Disease Surveillance, Antimicrobial Resistance Data Analysis, Network Meta-Analyses

Selected Publications

Google Scholar Page

*Hu, D., Cheng, T.Y., *Morris, P., Zimmerman, J., Wang, C. (2021) Active regional surveillance for early detection of exotic/emerging pathogens of swine: A comparison of statistical methods for farm selection, Preventive Veterinary Medicine, 187: 105233. DOI:10.1016/j.prevetmed.2020.105233.

*Goren, E., Wang, C., He, Z., Sheflin, A.M., Chiniquy, D., Prenni, J.E., Tringe, S., Schachtman, D.P., Liu, P. (2021) Feature selection and causal analysis for microbiome studies in the presence of confounding using standardization. BMC Bioinformatics, 22, 362. DOI:10.1186/s12859-021-04232-2

*Ji, J., Wang, C., Rotolo, M., Zimmerman, J. (2020) Modeling the Regional Disease Spread Over Time Using a Dynamic Spatio-temporal Model with an Application in Porcine Epidemic Diarrhea Virus data collected in Iowa, U.S. Preventive Veterinary Medicine, 181:105053. DOI:10.1016/j.prevetmed.2020.105053.

*Zhang, M., Wang, C., O’Connor, A. (2020) A hierarchical Bayesian latent class mixture model with censorship for detection of linear temporal changes in antibiotic resistance. PLOS ONE 15(1): e0220427, Antimicrobial Resistance Collection. DOI:10.1371/journal.pone.0220427.

*Ji, J., Wang, C., He, Z., Hay, K., Barnes, T., O'Connor, A.M. (2020) Comparing the estimates of effect obtained from statistical causal inference methods: An example using bovine respiratory disease in feedlot cattle. PLOS ONE, 15(6):e0233960. DOI:10.1371/journal.pone.0233960.

*Hu, D., Wang, C., O’Connor, A.M. (2020) A method of back-calculating the log odds ratio and standard error of the log odds ratio from the reported group-level risk of disease. PLOS ONE 15(3): e0222690. DOI:10.1371/journal.pone.0222690.

*Sun, Y., Wang, C., Meeker, W.Q., Morris, M., Zimmerman, J. (2019). A Latent Spatial Piecewise Exponential Model for Interval-Censored Disease Surveillance Data with Time-Varying Covariates and Misclassification. Statistics and Its Interface, 12(1):11-19. DOI:10.4310/SII.2019.v12.n1.a2.

Wang, C., Turnbull, B. W., Nielsen, S. S., Gröhn, Y. T., (2011). Bayesian analysis of longitudinal Johne’s disease diagnostic data without a gold standard test. Journal of Dairy Science, 94:2320-2328. DOI:10.3168/jds.2010-3675

Wang, C., Turnbull, B. W., Gröhn, Y. T., Nielsen, S. S. (2007). Nonparametric estimation of ROC curves based on Bayesian models when the true disease state is unknown. Journal of Agricultural, Biological, and Environmental Statistics, 12:128–146. DOI:10.1198/ 108571107X178095

Wang, C., Turnbull, B. W., Gröhn, Y. T., Nielsen, S. S. (2006). Estimating receiver operating characteristic curves with covariates when there is no perfect reference test for diagnosis of Johne's disease. Journal of Dairy Science, 89:3038–3046.  DOI:10.3168/jds.S0022-0302(06)72577-2