**Professor of Statistical Science**

Dr. John W. Seaman, Jr. CV

Marrs McLean 163

(254) 710-6181

[email protected]

# John W. Seaman, Jr., Ph.D.

## Professor of Statistical Science

**Education**

Ph.D., Mathematical Sciences, University of Texas at Dallas, 1983

M.S., Mathematical Sciences, University of Texas at Dallas, 1979

B.S., Mathematical Sciences, University of Texas at Dallas, 1978

**Major area of research**

Bayesian Inference, with an Emphasis on Biomedical Applications

**Courses currently teaching**

• 5360 Bayesian Methods for Data Analysis

• 5364 Survival and Reliability Theory

• 6351 Large Sample Theory

• 6352 Bayesian Theory

**Biography**

As a statistician, I have had the pleasure of delving into a broad spectrum of scientific problems, from evolutionary biology to engineering to drug development. Thinking about such a variety of problems is the chief attraction of statistical science for me. To share that enthusiasm with graduate and undergraduate students is a pleasure.

In the department, I spend much of my time directing dissertation research. I also enjoy working on research with my former students, many of whom have become like an extended family.

I am a member of the American Statistical Association, the American Association for the Advancement of Science, and the Union of Concerned Scientists. Personally, I enjoy reading, especially history and science, hiking, and scale model building.

**Selected Publications**

Natanagara, F., Neuenschwander, B., Seaman, J., Kinnnersley, N., Heilmann, C., Ohlssen, D., Rochester, G. (2014) "The current state of Bayesian methods in medical product development: survey results and recommendations from the DIA Bayseian Scientific Working Group," *Pharmaceutical Statistics*, **13**: 3-12.

Stamey, James D., Daniel P. Beavers, Douglas Faries, Karen L. Price, and John W. Seaman, Jr. (2014) "Bayesian modeling of cost-effectiveness studies with unmeasured confounding: a simulation study." *Pharmaceutical Statistics*, **13**, 94-100.

Bennett, M., Crowe, B., Price, K., Stamey, J., and Seaman, J. (2013). Comparison of Bayesian and frequentist meta-analytical approaches for analyzing time to event data, *Journal of Biopharmaceutical Statistics*, **23**, 129-145.

Faries,D., Peng, X., Pawaskar, M., Price, K., Stamey, J.D., and Seaman, Jr., J.W. (2013) Evaluating the Impact of Unmeasured Confounding with Internal Validation Data: An Example Cost Evaluation in Type 2 Diabetes. *Value in Health*, 16 (2), 259-266.

Stamey, J.D., Natanagara, F., Seaman, J.W. (2013). Bayesian sample size determination for a clinical trial with correlated continuous and binary outcomes. *Journal of Biopharmaceutical Statistics*, 23, 790-803.

Seaman, J. III, Seaman, J., and Stamey, J. (2012) Hidden dangers of specifying noninformative priors,* The American Statistician*, 66, 77-84.

Spann, M., Lindborg, S., Seaman, J., Baker, R., Dunayevich, E., and Breier, A., (2009) “Bayesian adaptive non-inferiority with safety assessment: retrospective case study to highlight potential benefits and limitations of the approach,” *J. of Psychiatric Research*, 43, 561-567.

Holt, M., Stamey, J., Seaman, J., and Young, D. (2009) "Bayesian test and sample size determination methods for binary outcomes in fixed-dose combination drug studies," *Journal of Biopharmaceutical Statistics*, **19**, 120-132.

Lavery, A., Barnes, S., Keith, M., Seaman J., and Armstrong, D. (2008) Prediction of healing for complex diabetic foot wounds based on early wound area progression: *Diabetes Care*, 31, 26-29.

Stamey, J., Seaman, J., and Young, D. (2008); A Bayesian approach to adjust for diagnostic misclassification between two mortality causes in Poisson regression; *Statistics in Medicine*, 27, 2440-2452.

McGlothlin, A., Stamey, J., and Seaman, J. (2008). Binary regression with misclassified response and covariate subject to measurement error: a Bayesian approach; *Biometrical Journal*, 50, 123-134.

Stamey, J., Seaman, J., and Young, D. (2007) Bayesian estimation of intervention effect with pre and post misclassified binomial data, *Journal of Biopharmaceutical Statistics*, 11, 93-108.

Stamey, J., Seaman, J., and Young, D. (2006). Bayesian inference for a correlated 2x2 table with a structural zero, *Biometrical Journal*, 48, 233-244.

Barnes, S., Lindborg, S., and Seaman, J. (2006) Multiple Imputation Techniques in Small Sample Clinical Trials, *Statistics in Medicine*, 25, #2, 233-245.

Stamey, J., Seaman, J., and Young, D. (2005) Bayesian analysis of complementary Poisson rate parameters with data subject to misclassification. *Journal of Statistical Planning and Inference*, 134, 36-48.

Stamey, J., Seaman, J., and Young, D. (2005) Bayesian sample size determination for inference on two binomial populations with no gold standard classifier. *Statistics in Medicine*, 24(19): 2963-2976.

Manner, D., Seaman, J., and Young, D. (2004) Bayesian Methods for Regression Using Surrogate Variables. *Biometrical Journal*, 46, 750-759.

Holt, M., Stamey, J., Seaman, J., and Young, D. (2004) A note on tests for interaction in quantal response data,” *J. of Statistical Computation and Simulation*, 74, 683-690.

Umble, L., Seaman, J., & Martz, H. “A distirbution-free Bayesian approach for determining the joint probability of failure of materials subject to multiple proof loads,” *Technometrics*, 41, 183-191, 1999.

Laviolette, M., Seaman, J., Woodall, W., and Barrett, J. “Issues Regarding the Use of Fuzzy Methods,” with discussants and reply in *Technometrics*, 37, 249-292, 1995 (Awarded the Youden Prize for Best Expository Paper, 1996).