STATISTICS FACULTY AT BOWLING GREEN STATE UNIVERSITY

Department of Applied Statistics and Operations Research

Nancy S. Boudreau joined the Department in 1980, having obtained her Ph.D. from the University of Florida under the direction of Professor John Saw. She has been the Director of the Statistical Consulting Center on campus since 1986. Her interests include categorical data analysis, regression analysis, and design of experiments. Selected publications include:

• A simulation study of a test for the equality of the coefficients of variation, with J. A. Sullivan. Communications in Statistics: Simulation and Computation, 15 (1986), 681-695.
• The impact of teachers in economic classrooms, with M. N. Browne, J. H. Hoag, and M. W. Wheeler. The Journal of Economics, XVII (1991), 25-30.
• Mapping the arrangement of chromatin by computer-aided microscopy, with C. A. Heckman, J. B. Olesen, J. Hasley, and S. Herber. Journal of Computer Assisted Microscopy, Dec., (1995).
• Critical modeling principles when testing for gender equity in faculty salary, with W. Balzer, P. Hutchinson, A. M. Ryan, T. Thorsteinson, J. A. Sullivan, R. Yonker, and D. Snavely. Research in Higher Education, 37, No. 6, (1996).
• Should faculty rank be included as a predictor variable in studies of gender equity in university faculty salaries, with J. A. Sullivan, W. Balzer, A. M. Ryan, R. Yonker, T. Thorsteinson, and P. Hutchinson. Research in Higher Education, 38, No. 3, (1997).

Jane Y. Chang joined the Department in 2001, having obtained her Ph.D. from The Ohio State University in 1989. Her interests are in the optimal design of experiments, design and analysis of microarray experiments, and applied statistics. Selected publications:

• EL Hassan Ridouane, Antonio Campo, Y. J. Chang. Natural Convection Patterns in Right-angled Triangular Cavities with Heated Vertical Sides and Cooled Hypotenuses. To appear in Journal of Heat Transfer.
• Hsu, J., Y. J. Chang and T. Wang. Simultaneous Confidence Intervals for Differential Gene Expressions. To appear in Journal of Statistical Planning and Inference.
• Chang, Y. J. and J. Hsu. cDNA Experimental Design. To appear in DNA Microarrays and Statistical Genomic Techniques: Design, Analysis, and Interpretation of Experiments. Allison/Page/Beasley/Edwards editors. Marcel-Dekker, New York.
• Hsu, J., Y. J. Chang and T. Wang Multiple Comparisons in Screening for Active Genes from Microarray Experiments. To appear in Screening, Angela Dean and Sue Lewis editors, Springer Verlag.
• D. Lin and Chang, Y.J. A Note on Cyclic Orthogonal Designs (2001). Statistica Sinica Vol. 11, No. 2, 549-552.

• Yeh, A. B., Lin, D. K. J., and McGrath, R. N. (2006) Multivariate Control Charts for Monitoring Covariance Matrix: A Review, Quality Technology and Quantitative Management, 3, 415-436.
• McGrath, R. N. and Yeh, A. B. (2005) A Quick, Compact, Two-Sample Dispersion Test: Count Five”, The American Statistician, 59, 47-53.
• McGrath, R. N. and Lin, D. K. J. (2003) Analyzing Location and Dispersion in Unreplicated Fractional Factorials, Statistics and Probability Letters, 65, 369-377.Ê
• McGrath, R. N. (2003). Separating Location and Dispersion Effects in Unreplicated Fractional Factorials, Journal of Quality Technology, 35, 306-316.Ê
• McGrath, R. N., and Lin, D. K. J. (2001). Testing Multiple Dispersion Effects in Unreplicated Fractional Factorial Designs, Technometrics, 43, pp 406-414.

Ken Ryan earned a Ph.D. in Statistics from Iowa State University in 2001. Just prior to joining the department in 2006, he worked at Information Resources, a Chicago-based marketing research organization. His research interests are Bayesian data analysis, design of experiments, random effect models, and statistical computing. Representative publications:

• Ryan, K.J. (2003), ``Estimating Expected Information Gains for Experimental Designs with Application to the Random Fatigue-Limit Model,'' The Journal of Computational and Graphical Statistics, 12, 3, 585-603.
• Ryan, K.J. (2003), ``Some Flexible Families of Intensities for Nonhomogeneous Poisson Process Models and Their Bayes Inference,'' Quality & Reliability Engineering International, 19, 171-181.
• Reese, C.S., Wilson, A.G., Hamada, M., Martz, H.F., and Ryan, K.J. (2004), ``Integrated Analysis of Computer and Physical Experiments,'' Technometrics, 46, 2, 153-164.
• Miescke, K.J. and Ryan, K.J. (2006), ``On the Performance of Gupta's Subset Selection Rule," JSPI, 136, 2004-2019.
• Ryan, K.J. and Bulutoglu, D.A. (2006), ``E(s^2)-Optimal Supersaturated Designs with Good Minimax Properties," (Accepted for publication in JSPI)

Arthur Yeh joined the Department in 1993, having obtained his Ph.D. from Rutgers University in 1993 under the direction of Professor Kesar Singh. His research interests include bootstrap, data depth, optimal experimental designs, statistical process control, and statistical computing. Selected publications:

• A two-stage design for the construction of D-optimal experimental designs, with G. Montepiedra, Communications in Statistics: Simulation and Computation, to appear in 1998.
• A robust process capability index, with S. Bhattacharya, Communications in Statistics: Simulation and Computation, to appear in 1998.
• A bootstrap procedure in linear regression with nonstationary errors, The Canadian Journal of Statistics, to appear in 1998.
• Balanced confidence regions based on data depth and the bootstrap, with K. Singh, Journal of the Royal Statistical Society, Series B, 59 (1997), 639-652.
• Bootstrap percentile confidence bands based on the concept of curve depth, Communications in Statistics: Simulation and Computation, 25 (1996), 905-922.