sometext

Department of Statistics
216 LeConte College
1523 Greene St.
University of South Carolina
Columbia, SC 29208

Office: LeConte 219C
Phone (803) 777-3859
e-mail: hansont@stat.sc.edu.

Publications

Chen, Y., Sun, M., and Hanson, T. Nonparametric multivariate Polya tree EWMA control chart for process changepoint detection. Statistics and Its Interface, accepted.

Zhou, H. and Hanson, T. A unified framework for fitting Bayesian semiparametric models to arbitrarily censored survival data, including spatially-referenced data. Journal of the American Statistical Association, accepted.

McMahan, C., Tebbs, J., Hanson, T., and Bilder, C. Bayesian regression for group testing data. Biometrics, accepted.

Chen, Y. and Hanson, T. Flexible parametrization of variance functions for quantal response data derived from counts. Journal of Biopharmaceutical Statistics, accepted.

Chen, Y. and Hanson, T. (2017). Copula regression models for discrete and mixed bivariate responses. Journal of Statistical Theory and Practice, 11, 515-530.

Zhou, H., Hanson, T., and Zhang, J. (2017). Generalized accelerated failure time spatial frailty model for arbitrarily censored data. Lifetime Data Analysis, 23, 495-515.

Hanson, T., de Carvalho, M., and Chen, Y. (2017). Bernstein polynomial angular densities of multivariate extreme value distributions. Statistics and Probability Letters, 128, 60-66.

Bao, J., Hanson, T., McMillan, G., and Knight, K. (2017). Assessment of DPOAE test-retest difference curves via hierarchical Gaussian processes. Biometrics, 73, 334-343.

Cipolli, W. and Hanson, T. (2017). Computationally tractable approximate and smoothed Polya trees. Statistics and Computing, 27, 39-51.

Chen, Y. and Hanson, T. (2017). Semiparametric regression control charts. Journal of Statistical Theory and Practice,11, 126-144.

Liu, J., Liu, S., Zhou, H., Hanson, T., Yang, L., Chen, Z., and Zhou, M. (2016). Association of green tea consumption with mortality from all-cause, cardiovascular disease and cancer in a Chinese cohort of men. European Journal of Epidemiology, 31, 853-865.

Bao, J. and Hanson, T. (2016). A mean-constrained finite mixture of normals. Statistics and Probability Letters, 117, 93-99.

Cipolli, W., Hanson, T., and McLain, A. (2016). Bayesian nonparametric multiple testing. Computational Statistics & Data Analysis, 101, 64-79.

Zhou, H., Hanson, T., and Knapp, R. (2015). Marginal Bayesian nonparametric model for time to disease arrival of threatened amphibian populations. Biometrics, 71, 1101-1110.

Fowler, J., Cipolli, W., and Hanson, T. (2015). A comparison of three diagnostic tests for diagnosis of carpal tunnel syndrome using latent class analysis. Journal of Bone & Joint Surgery, 97, 1958-1961.

Branscum, A., Johnson, W., Hanson, T., and Baron, A. (2015). Flexible regression models for ROC and risk analysis, with or without a gold standard. Statistics in Medicine, 34, 3997-4015.

Hanson, T., Banerjee, S., Li, P., and McBean, A. (2015). Spatial boundary detection for areal counts. In Nonparametric Bayesian Methods in Biostatistics and Bioinformatics (Frontiers in Probability and the Statistical Sciences), pp. 377-399. R. Mitra and P. Müller, editors. Springer: Switzerland.

Zhou, H. and Hanson, T. (2015). Bayesian spatial survival models. In Nonparametric Bayesian Methods in Biostatistics and Bioinformatics (Frontiers in Probability and the Statistical Sciences), pp. 215-246. R. Mitra and P. Müller, editors. Springer: Switzerland.

Bao, J. and Hanson, T. (2015). Bayesian nonparametric multivariate ordinal regression. Canadian Journal of Statistics, 43, 337-357.

Müller, P., Quintana, F., Jara, A., and Hanson, T. (2015). Bayesian Nonparametric Data Analysis. Springer: Switzerland.

Li, L., Hanson, T., and Zhang, J. (2015). Spatial extended hazard model with application to prostate cancer survival. Biometrics, 71, 313-322.

Zhou, H., Hanson, T., Jara, A., and Zhang, J. (2015). Modelling county level breast cancer survival data using a covariate-adjusted frailty proportional hazards model. Annals of Applied Statistics, 9, 43-68.

Zantek, P., Hanson, T., Damien, P., and Popova, E. (2015). A decision dependent stochastic process model for repairable systems with applications. Operations Research Perspectives, 2, 73-80.

Li, P., Banerjee, S., Hanson, T., and McBean, A. (2015). Bayesian hierarchical models for detecting boundaries in areally referenced spatial datasets. Statistica Sinica, 25, 385-402.

Chen, Y. and Hanson, T. (2014). Bayesian nonparametric density estimation for doubly-truncated data. Statistics and Its Interface, 4, 455-463.

Hanson, T., Branscum, A., and Johnson, W. (2014). Informative g-priors for logistic regression. Bayesian Analysis, 9, 597-612.

Li, L., Hanson, T., Damien, P., and Popova, E. (2014). A Bayesian nonparametric test for minimal repair. Technometrics, 56, 393-406.

Chen, Y., Hanson, T., and Zhang, J. (2014). Accelerated hazards model based on parametric families generalized with Bernstein polynomials. Biometrics, 70, 192-201.

McMillan, G. and Hanson, T. (2014). Sample size requirements for establishing clinical test-retest standards. Ear and Hearing, 35, 283-286.

Kirschenmann, T., Popova, E., Damien, P., and Hanson, T. (2014). Decision dependent stochastic processes. European Journal of Operational Research, 234, 731-742.

Li, L. and Hanson, T. (2014). A Bayesian semiparametric regression model for reliability data using effective age. Computational Statistics and Data Analysis, 73, 177-188.

Xu, L., Bedrick, E., Hanson, T., and Restrepo, C. (2014). A comparison of statistical tools for identifying modality in body mass distributions. Journal of Data Science, 12, 175-196.

Chen, Y. and Hanson, T. (2014). Bayesian nonparametric k-sample tests for censored and uncensored data. Computational Statistics and Data Analysis, 71, 335-346.

Inacío de Carvalho, V., Jara, A., Hanson, T., and de Carvalho, M. (2013). Bayesian nonparametric ROC regression modeling. Bayesian Analysis, 8, 623-646.

McMillan, G., Hanson, T., Saunders, G., and Gallun, F. (2013). A two-component circular regression model for repeated measures auditory localization data. Journal of the Royal Statistical Society: Series C, 62, 515-534.

Schörgendorfer, A., Branscum, A., and Hanson, T. (2013). A Bayesian goodness of fit test and semiparametric generalization of logistic regression with measurement data. Biometrics, 69, 508-519.

Boyer, T., Hanson, T., and Singer, R. (2013). Estimation of low quantity genes: A hierarchical model for analyzing censored quantitative real-time PCR data. PLoS One, 8(5): e64900.

Hanson, T. and Jara, A. (2013). Surviving fully Bayesian nonparametric regression models. In Bayesian Theory and Applications, pp. 593-615. P. Damien, P. Dellaportas, N. Polson, and D. Stephens, eds. Oxford University Press: Oxford.

Hanson, T., Jara, A., and Zhao, L. (2012). A Bayesian semiparametric temporally stratified proportional hazards model with spatial frailties. Bayesian Analysis, 7, 147-188.

Liimatainen, T., Sierra, A., Hanson, T., Sorce, D., Ylä-Herttuala, S., Garwood, M., Michaeli, S., Gröhn, O. (2012). Glioma cell density in a rat gene therapy model gauged by water relaxation rate along a fictitious magnetic field. Magnetic Resonance in Medicine, 67, 269-277.

Hanson, T. and McMillan, G. (2012). Scheffe style simultaneous credible bands for regression surfaces with application to Ache honey gathering, Journal of Data Science, 10, 175-193.

Buijze, G., Mallee, W., Beeres, F., Hanson, T., Johnson, W., and Ring, D. (2011). Diagnostic performance tests for suspected scaphoid fractures differ with conventional and latent class analysis. Clinical Orthopaedics and Related Research, 469, 3400-3407.

Jara, A. and Hanson, T. (2011). A class of mixtures of dependent tailfree processes. Biometrika, 98, 553-566.

Shrivastava, D., Hanson, T., Kulesa, J., Tian, J., Adriany, G., and Vaughan, J.T. (2011). Radiofrequency heating in porcine models with a "Large" 32 cm internal diameter, 7 T (296 MHz) head coil. Magnetic Resonance in Medicine, 66, 255-263.

Zhao, L. and Hanson, T. (2011). Spatially dependent Polya tree modeling for survival data. Biometrics, 67, 391-403.

McMillan, G., Saunders, G., and Hanson, T. (2011). A statistical model of horizontal auditory localization performance data. Journal of the Acoustical Society of America, 129, EL229-EL235.

Jara, A., Hanson, T., Quintana, F., Müller, P., and Rosner, G. (2011). DPpackage: Bayesian non- and semi-parametric modelling in R. Journal of Statistical Software, 40, 1-30.

Hanson, T., Monteiro, J., and Jara, A. (2011). The Polya tree sampler: Towards efficient and automatic independent Metropolis-Hastings proposals. Journal of Computational and Graphical Statistics, 20, 41-62.

Li, M. and Hanson, T. (2011). Bayesian nonparametric multivariate statistical models for testing association between quantitative traits and candidate genes in structured populations. Journal of the Royal Statistical Society: Series C, 60, 207-219.

Johnson, W., Branscum, A., and Hanson, T. (2011). Rejoinder for "Predictive comparison of joint longitudinal-survival modeling: a case study illustrating competing approaches." Lifetime Data Analysis, 17, 37-42.

Hanson, T., Branscum, A., and Johnson, W. (2011). Predictive comparison of joint longitudinal-survival modeling: A case study illustrating competing approaches (with discussion). Lifetime Data Analysis, 17, 3-18.

Buijze, G., Hanson, T., Johnson, W., and Ring, D. (2010). Latent class analysis to determine the accuracy of diagnostic tests in orthopaedics. Orthopaedic Journal at Harvard Medical School, 12, 106-108.

Ghosh, P. and Hanson, T. (2010). A semiparametric Bayesian approach to multivariate longitudinal data. Australian and New Zealand Journal of Statistics, 52, 275-288.

Jones, G., Johnson, W., Hanson, T., and Christensen, R. (2010). Identifiability of models for multiple diagnostic testing in the absence of a gold standard. Biometrics, 66, 855-863.

Li, M., Reilly, C., and Hanson, T. (2010). Association tests for a censored quantitative trait and candidate genes in structured populations with multilevel genetic relatedness. Biometrics, 66, 925-933.

Xu, L., Hanson, T., Bedrick, E., and Restrepo, C. (2010). Hypothesis tests on mixture model components with applications in ecology and agriculture. Journal of Agricultural, Biological, and Environmental Statistics, 15, 308-326.

Shrivastava, D., Abosch, A., Hanson, T., Tian, J., Gupte, A., Iaizzo, P., and Vaughan, J.T. (2010). Effect of the extracranial deep brain stimulation lead on radiofrequency heating at 9.4 Tesla (400.2 MHz). Journal of Magnetic Resonance Imaging, 32, 600-607.

Rafati, N., Mehranabi-Yeganeh, H., and Hanson, T. (2010). Risk factors for abortion in dairy cows from commercial Holstein dairy herds in the Tehran region. Preventive Veterinary Medicine, 96, 170-178.

Nestrasil, I., Michaeli, S., Liimatainen, T., Rydeen, C., Kotz, C., Nixon, J., Hanson, T., and Tuite, P. (2010). T and T MRI in the evaluation of Parkinson's disease. Journal of Neurology, 257, 964-968.

Christensen, R., Johnson, W., Branscum, A., and Hanson, T. (2010). Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians. CRC Press, Boca Raton.

Baab, K., Freidline, S., Wang, S., and Hanson, T. (2010). Relationship of cranial robusticity to cranial form, geography and climate in Homo sapiens. American Journal of Physical Anthropology, 141, 97-115.

Popova, E., Morton, D., Damien, P., and Hanson, T. (2010). Bayesian analysis and decisions in nuclear power plant maintenance. InThe Oxford Handbook of Applied Bayesian Analysis, 219-240. A. O'Hagan, and M. West, eds. Oxford University Press: Oxford.

Jara, A., Hanson, T., and Lesaffre, E. (2009). Robustifying generalized linear mixed models using a new class of mixtures of multivariate Polya trees. Journal of Computational and Graphical Statistics, 18, 838-860.

Shrivastava, D., Hanson, T., Kulesa, J., DelaBarre, L., Snyder, C., and Vaughan, T.J. (2009). Radio-frequency heating at 9.4T: In vivo thermoregulatory temperature response in swine. Magnetic Resonance in Medicine, 62, 888-895.

Zhao, L., Hanson, T., and Carlin, B. (2009). Flexible spatial frailty modeling via mixtures of Polya trees. Biometrika, 96, 263-276.

Singer, R., Mayer, A., Hanson, T., and Isaacson, R. (2009). Do microbial interactions and cultivation media decrease the accuracy of Salmonella surveillance systems and outbreak investigations? Journal of Food Protection, 72, 707-713.

Hanson, T., Johnson, W., and Laud, P. (2009). Semiparametric inference for survival models with step process covariates. Canadian Journal of Statistics, 37, 60-79.

Muñoz-Zanzi, C., Trampel, D., Hanson, T., Harrison, K., Goyal, S., Cortinas, R., and Lauer, D. (2009). Field estimation of the flock-level diagnostic specificity of an enzyme-linked immunosorbent assay for Avian metapneumovirus antibodies in turkeys. Journal of Veterinary Diagnostic Investigation, 21, 240-243.

Michaeli, S., Burns, T.C., Kudishevich, E., Hanson, T., Sorce, D.J., Garwood, M., and Low, W.C. (2009). Detection of neuronal loss using T MRI assessment of 1H2O spin dynamics in the aphakia mouse model. Journal of Neuroscience Methods, 177, 160-167.

Johnson, T.E., Kassie, F., O'Sullivan, G., Negia, M., Hanson, T.,Upadhyaya, P., Ruvolo, P.P., Hecht, S.S., Xing, C. (2008). Chemopreventive effect of kava on 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone plusbenzo[a]pyrene-induced lung tumorigenesis in A/J mice. Cancer Prevention Research, 1, 430-438.

Li, M., Reilly, C., and Hanson, T. (2008). A semiparametric test to detect associations between quantitative traits and candidate genes in structured populations. Bioinformatics, 24, 2356-2362.

Christensen, R., Hanson, T., and Jara, A. (2008). Parametric nonparametric statistics: An introduction to mixtures of finite Polya trees. The American Statistician, 62, 296-306.

Branscum, A. and Hanson, T. (2008). Bayesian nonparametric meta-analysis using Polya tree mixture models. Biometrics, 64, 825-833.

Yang, M., Hanson, T., and Christensen, R. (2008). Nonparametric Bayesian estimation of a bivariate density with interval censored data. Computational Statistics and Data Analysis, 52, 5202-5214.

Branscum, A., Johnson, W., Hanson, T., and Gardner, I. (2008).Bayesian semiparametric ROC curve estimation and disease risk assessment. Statistics in Medicine, 27, 2474-2496.

Branscum, A., Hanson, T., and Gardner, I. (2008). Bayesian nonparametric models for regional prevalence estimation. Journal of Applied Statistics, 35, 567-582.

Hanson, T., Branscum, A., and Gardner, I. (2008). Multivariate mixtures of Polya trees for modelling ROC data. Statistical Modelling, 8, 81-96.

Hanson, T., Kottas, A., and Branscum, A. (2008). Modelling stochastic order in the analysis of receiver operating characteristic data: Bayesian nonparametric approaches. Journal of the Royal Statistical Society: Series C, 57, 207-225.

Shrivastava, D., Hanson, T., Schlentz, R., Gallagher,W., Snyder, C., DelaBarre, L., Prakash, S., Iaizzo, P., and Vaughan, J.T. (2008). Radiofrequency heating at 9.4T: In vivo temperature measurement results in swine. Magnetic Resonance in Medicine, 59, 73-78.

Hanson, T. and Pearson, O. (2007). Fitting MANOVA models with missing continuous or ordinal data using reference priors.Communications in Statistics: Simulation and Computation, 36, 621-630.

McMillan, G., Hanson, T., and Lapham, S. (2007). Geographic variability inalcohol-related crashes in response to legalized Sunday packaged alcohol sales in New Mexico. Accident Analysis and Prevention, 39, 252-257.

Damien, P., Galenko, A., Popova, E., and Hanson, T. (2007). Bayesian semiparametric analysis for a single item maintenance optimization. European Journal of Operational Research,182, 794-805.

Hanson, T. and Yang, M. (2007). Bayesian semiparametric proportional odds models. Biometrics, 63, 88-95.

Hanson, T. (2007). Polya trees and their use in reliaiblity and survival analysis. In Encyclopedia of Statistics in Quality and Reliability, 1385-1390. F. Ruggeri, R. Kenett and F.W. Faltin, eds. John Wiley & Sons Ltd., Chichester, UK.

Hanson, T., Johnson, W., and Laud, P. (2007). A semiparametric accelerated failure time model for survival data with time dependent covariates. In Bayesian Statistics and its Applications, 254-269. S.K. Upadhyay, U. Singh, and D.K. Dey, eds. New Delhi: Anamaya Publishers.

Hanson, T. (2006). Inference for mixtures of finite Polya tree models. Journal of the American Statistical Association, 101, 1548-1565.

Hanson, T. (2006). Modeling censored lifetime data using a mixture of gammas baseline. Bayesian Analysis, 1, 575-594.

Hanson, T., Johnson, W., and Gastwirth, J. (2006). Bayesian inference for prevalence and diagnostic test accuracy based on dual-pooled screening. Biostatistics, 7, 41-57.

McMillan, G., Hanson, T., Bedrick, E., and Lapham, S. (2005). Using the bivariate Dale model to jointly estimate predictors of frequency and quantity of alcohol use. Journal of Studies on Alcohol, 65, 643-650.

McMillan, G. and Hanson, T. (2005). SAS macro BDM for fitting the Dale regression model to bivariate ordinal response data. Journal of Statistical Software, 14, 1-12.

Hanson, T., Sethuraman, J., and Xu, L. (2005). On choosing the centering distribution in Dirichlet process mixture models. Statistics and Probability Letters, 72, 153-162.

Thurmond, M., Branscum, A., Johnson, W., Bedrick, E. and Hanson, T. (2005). Predicting the probability of abortion in dairy cows: A hierarchical Bayesian logistic-survival model using sequential pregnancy data. Preventive Veterinary Medicine, 68, 223-239.

Hanson, T., Branscum, A., and Johnson, W. (2005). Bayesian nonparametric modeling and data analysis: an introduction. In Bayesian Thinking: Modeling and Computation (Handbook of Statistics, volume 25), 245-278. D.K. Dey and C.R. Rao, eds. Amsterdam: Elsevier.

Johnson, W. and Hanson, T. (2005). Comment on "On model expansion, model contraction, identifiability and prior information: Two illustrative scenarios involving mismeasured variables," by Paul Gustafson. Statistical Science, 20, 131-134.

Marks, S., Hanson, T., and Melli, A. (2004). Comparison of direct immunofluorescence, modified acid-fast staining, and enzyme immunoassay techniques for detection of Cryptosporidium spp innaturally exposed kittens. Journal of the American Veterinary Medical Association, 225, 1549-1553.

Hanson, T. & Johnson, W. (2004). A Bayesian semiparametric AFT model for interval censored data. Journal of Computational and Graphical Statistics, 13, 341-361.

Hanson, T., Johnson, W., Gardner, I., and Georgiadis, M. (2003). Determining the infection status of a herd. Journal of Agricultural, Biological, and Environmental Statistics, 8, 469-485.

Hanson, T., Johnson, W., and Gardner, I. (2003). Hierarchical models for estimating herd prevalence and test accuracy in the absence of a gold-standard. Journal of Agricultural, Biological, and Environmental Statistics, 8, 223-239.

Hanson, T., Bedrick, E., Johnson, W., and Thurmond, M. (2003). A mixture model for bovine abortion and fetal survival. Statistics in Medicine, 22, 1725-1739.

Hanson, T. and Johnson, W. (2002). Modeling regression error with a mixture of Polya trees. Journal of the American Statistical Association, 97, 1020-1033.

Schölnberger, H., Menache, G., and Hanson, T. (2001). A biomathematical modeling approach to explain the phenomenon of radiation hormesis. Human and Ecological Risk Assessment, 7, 867-890.

Schölnberger, H., Scott, B., and Hanson, T. (2001). Application of Bayesian inference to characterize risks associated with low doses of low-LET radiation. Bulletin of Mathematical Biology,63, 865-883.

Johnson, W., Hanson, T., Gastwirth, J. and Gardner, I. (2001). Pooled sample screening with quality control. In Bayesian methods with applications to science, policy, and official statistics, 253-261. E. George and P. Nanopoulos, eds. Official Publications of the European Communities, Luxembourg.

Hanson, T., Johnson, W., and Gardner, I. (2000). Log-linear and logistic modeling of dependence among diagnostic tests. Preventive Veterinary Medicine, 45, 123-137.