3225 Daniel Avenue Avenue
P O Box 750332
Dallas, Texas 75275-0332
Phone: 214-768-2451 Fax: 214-768-4035
Ph.D., Statistics, University of Missouri, Columbia, 2005
· Cao, J. and Stokes, S.L. (2008). Bayesian IRT guessing models for partial guessing behaviors. Psychometrika, 73, 209-230.
· Cao, J., He, C., and McCoy, T. (2008). Bayesian estimation of age-specific bird nest survival rates with categorical covariates. Environmental and Ecological Statistics, 15, 49-58.
· Cao, J., Xie, X., Zhang, S., Whitehurst, A., and White, M. (2009). Bayesian optimal discovery procedure for simultaneous significance testing. BMC Bioinformatics, 10:5.
· Zhang, S and Cao, J. (2009). A close examination of double filtering with fold change and t test in microarray analysis. BMC Bioinformatics, 10:402.
· Livingston, E.H., Elliot, A.C., Hynan, L.S., and Cao, J. (2009). Effect size estimation: necessary component of statistical analysis. Archives of Surgery, 144, 706-712.
· Cao, J., Lee, J.J., and Albert, S. (2009). Comparison of Bayesian sample size determination criteria: ACC, ALC, and WOC. Journal of Statistical Planning and Inference, 139, 4111-4122.
· Cao, J., He, C., Suedkamp Wells, K.M., Millspaugh, J.J., and Ryan, M.R. (2009). Modeling age and nest-specific survival using a hierarchical Bayesian approach. Biometrics, 65, 1052-1062.
· Zhang, S., Cao, J., Kong, M., and Scheuermann, R.H. (2010). GO-Bayes: Gene Ontology-based over-representation analysis using a Bayesian approach. Bioinformatics, 26, 905-911.
· Cao, J., Moosman, A., and Johnson, V.E. (2010). A Bayesian goodness-of-fit test for censored data. Biometric, 66, 426-434.
· Cao, J., Stokes, S.L., and Zhang, S. (2010). A Bayesian approach to ranking and rater evaluation: an application to grant reviews. Journal of Educational and Behavioral Statistics, 35, 194-214.
· Cao, J. and Stokes, S.L. (2010). Evaluation of wine judge performance through three characteristics: bias, discrimination, and variation. Journal of Wine Economics, 5(2), 1-11.
· Cao, J. and Zhang, S. (2010). Measuring statistical significance for full Bayesian methods in microarray analysis. Bayesian Analysis, 5, 413-428.
· Livingston, E.H. and Cao, J. (2010). Procedure volume as a predictor of surgical outcomes. Journal of the American Medical Association, 304, 95-97.
· Zhang, S., Cao, J., and Chul, A. (2010). Calculating sample size in trials using historical controls. Clinical Trials, 7, 343-353.
· Livingston, E.H., Cao, J., and Dimick, J.B. (2010). Tread carefully with stepwise regression. Archives of Surgery, 145, 1039-1040.
· Cao, J. (2011). Unbiased FDR for full Bayesian methods in microarray analysis. Twenty Seventy Southern Biomedical Engineering Conference Proceedings, 5:2.
· Zhang, S., Cao, J., and Ahn, C. (2013). Sample size calculation for studies comparing binary outcomes using historical controls. Biometrical Journal, 55, 190-202.
· Hodgson, R. and Cao, J. (2014). Criteria for accrediting expert wine judges. Journal of Wine Economics, 9(1), 62-74.
· Zhang, S., Cao, J., and Ahn, C. (2014). A GEE Approach to Determine Sample Size for Pre- and Post-Intervention Experiments with Dropout, Computational Statistics and Data Analysis, 69, 114-121.
· Cao, J. and Zhang, S. (2014). A Bayesian extension of the hypergeometric test for functional enrichment analysis. Biometrics, 70(1), 84-94.
· Cao, J. (2014). Quantifying randomness versus consensus among wine quality ratings. Journal of Wine Economics, 9(2), 202-213.
· Cao, J. and Zhang, S. (2014). Multiple comparison procedures. Journal of the American Medical Association, 312, 543-544.
· Olkin, I., Lou, Y., Stokes, L., and Cao, J. (2014). Analyses of wine-tasting data: a tutorial. Journal of Wine Economics, in press.
· Lou, Y., Cao, J., Zhang, S., and Ahn, C. (2015). Sample size calculations for time-averaged difference of longitudinal binary outcomes. Communications in Statistics – Theory and Methods, accepted.
· Zhang, S., Cao, J., and Ahn, C. (2015). Sample size calculation for before-after experiments with partially overlapping cohorts. Contemporary Clinical Trials, accepted.
· Lou, Y., Cao, J., Zhang, S., and Ahn, C. (2015), Sample size estimation for a two-group comparison of repeated count outcomes using GEE, Communications in Statistics – Theory and Methods, in press.
· Zhang, J.Zhang, S., A.J., G., C.N., H.Gu, Z., S.Klem, E.B.Scheuermann, R.H. (2016), Genetic Changes Found in a Distinct Clade of Enterovirus D68 Associated with Paralysis during the 2014 Outbreak, Virus Evolution, DOI: http://dx.doi.org/10.1093/ve/vew015
· R code to evaluate sample size and empirical power for 2-group comparison of slopes for clinical trials with a count outcome
· R code to evaluate sample size and empirical power for K-group comparison of slopes for clinical trials with a count outcome
Doctoral Students Supervised
· Ayman Ibrahim Al-Rawashdeh, “Semiparametric Bayesian Methods for Multivariate Survival Data”, 2013.
· Ying Lou, “Sample Size Estimation for Comparing Repeated Count Measurements Using GEE”, 2014.
· Yin Xi, “Bayesian Spatial Clustering Method and Its Application in Radiology”, 2015.
· Charles South, “A Dynamic Modelling and Optimization Approach to Daily Fantasy Basketball”, 2016.
All course material is available via Blackboard.