### 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 _{1ρ}* and

*T*MRI in the evaluation of Parkinson's disease.

_{2ρ}*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. In*The 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 _{1ρ}* MRI assessment of

^{1}H

_{2}O 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.