Baylor University
Department of Statistical Science
College of Arts & Sciences

Baylor > Statistical Science > Faculty Directory > Dr. James D. Stamey, Graduate Programs Director
Professor of Statistical Science

Graduate Program Director of Statistical Science Department

Dr. James D. Stamey CV

Marrs McLean 153
(254) 710-7405

James D. Stamey, Ph.D., Graduate Programs Director

Associate Professor of Statistical Science

B.S., Mathematics, Northwestern State University, 1995
M.B.A., Business, Baylor University, 1997
Ph.D., Statistics, Baylor University, 2000

Major area of research
Measurement Error and Misclassification, Bayesian Sample Size Determination

Courses currently teaching
• 5351 Theory of Statistics I
• 5352 Theory of Statistics II
• 5360 Bayesian Methods for Data Analysis


My principal area of research is in parameter estimation when data is subject to measurement error. This has application in areas as diverse as marketing, economics, epidemiology, and political science. Recent dissertations I have worked on have been inspired by current pharmaceutical research as well as problems in econometrics. Working on problems driven by real life applications is both exciting for me and a great opportunity for our students.

Outside of statistics I enjoy spending time with my family, watching and playing tennis, and attending Baylor sporting events. I am a member of Emmanuel Anglican Church.

Selected Publications

Cheng D, Branscum AJ, Stamey JD (2010) Accounting for Response Misclassification and Covariate Measurement Error Improves Power and Reduces Bias in Epidemiologic Studies, Annals of Epidemiology, 20, 562-567.

Stamey JD, Holt MM, (2010) Bayesian interval estimation for predictive values from case-control studies, Communications in Statistics, 31, 101-110.

Cheng D, Branscum AJ, Stamey JD (2010) A Bayesian approach to sample size determination for studies designed to evaluate continuous medical tests, Computational Statistics and Data Analysis, 2010, 54, 298-307.

Stamey, J.D., Bekele, B.N., Powers, S. (2009) Bayesian modeling of historical follow-up studies with missing data; Annals of Epidemiology, 19, 416-422.

Cheng, D., Stamey, J.D., Branscum, A.J. (2009) Bayesian approach to average power calculations for binary regression models with misclassified outcomes, Statistics in Medicine, 28, 848-863.

Turner, D., Stamey, JD, Young, DM (2009) Classic group testing with cost for grouping and testing, Computers and Mathematics with Applications, 58, 1930-1935.

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

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.

Stamey, J., Boese, D., and Young, D. (2008); Confidence intervals for parameters of two diagnostic tests in the absence of a gold standard; Computational Statistics and Data Analysis, 52, 1335-1346.

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.

Gerlach, R. and Stamey, J. (2007); Bayesian model selection for logistic regression with misclassified outcomes; Statistical Modeling, 7, 279-297.