Walter W. Piegorsch, Ph.D., PStat(ASA), is the Director of Statistical Research & Education at the University of Arizona’s BIO5 Institute. He is also a Professor of Mathematics, a Professor of Public Health, and a Member and former Chair of the University’s Graduate Interdisciplinary Program (GIDP) in Statistics. Dr. Piegorsch studies data science for environmental problems, with emphasis on informatics for environmental hazards and risk assessment. He coordinates these interests with his research translating quantitative risk analytics to problems in public health, including geo-spatially referenced disaster informatics; multiple/simultaneous inferences for toxicological and genetic endpoints; and the historical development of statistical thought as prompted by problems in the biological and environmental sciences. He currently leads a team developing statistical methods for estimating benchmark dose markers in environmental hazard analyses. This research has been funded by the U.S. National Institute of Environmental Health Sciences, the U.S. Environmental Protection Agency, and the U.S. National Cancer Institute. He also has constructed statistical models for data from transgenic bio-technologies, developed guidelines for the design of bioassays in select transgenic animal systems, and has proposed retrospective designs for analyzing gene-environment and gene-nutrient interactions in human population studies.
Piegorsch, W.W. Model uncertainty in environmental dose-response risk analysis. Statistics and Public Policy 1, 79-85 (2014).
Balakrishnan, N., Brandimarte, P., Everitt, B., Molenberghs, G., Piegorsch, W.W., and Ruggeri, F. (eds.) Wiley StatsRef: Statistics Reference Online, Chichester: John Wiley & Sons (2014).
Cutter, S.L., Emrich, C.T., Mitchell, J.T., Piegorsch, W.W., Smith, M.M., and Weber, L. Hurricane Katrina and the Forgotten Coast of Mississippi. Cambridge: Cambridge University Press (2014).
Piegorsch, W.W., An, L., Wickens, A.A., West, R.W., Peña, E.A., and Wu, W. Information-theoretic model-averaged benchmark dose analysis in environmental risk assessment. Environmetrics 24, 143-157 (2013).
El-Shaarawi, A.H. and Piegorsch, W.W. (eds.) Encyclopedia of Environmetrics, 2nd edn., Vols. 1-6. Chichester: John Wiley & Sons (2012).
Deutsch, R.C. and Piegorsch, W.W. Benchmark dose profiles for joint-action quantal data in quantitative risk assessment. Biometrics 68, 1313–1322 (2012).
Piegorsch, W.W., Xiong, H., Bhattacharya, R.N., and Lin, L. Nonparametric estimation of benchmark doses in environmental risk assessment. Environmetrics 23, 717–728 (2012).
West, R.W., Piegorsch, W.W., Peña, E.A., An, L., Wu, W., Wickens, A.A., Xiong, H., and Chen, W. The impact of model uncertainty on benchmark dose estimation. Environmetrics 23, 706-716 (2012).
Piegorsch, W.W. Translational benchmark risk analysis. Journal of Risk Research 13, 653-667 (2010).
Piegorsch, W.W. and Bailer, A.J. Combining information. Wiley Interdisciplinary Reviews: Computational Statistics 1, 354-360 (2009).
Buckley, B.E., Piegorsch, W.W., and West, R.W. Confidence limits on one-stage model parameters in benchmark risk assessment. Environmental and Ecological Statistics, 16, 53-62 (2009).
West, R.W., Nitcheva, D.K., and Piegorsch, W.W. Bootstrap methods for simultaneous benchmark analysis with quantal response data. Environmental and Ecological Statistics, 16, 63-73 (2009). P
iegorsch, W.W. and Schuler, E. Communicating the risks, and the benefits, of nanotechnology. International Journal of Risk Assessment and Management 10, 57-69 (2008).
Piegorsch, W.W., Cutter, S.L., and Hardisty, F. Benchmark analysis for quantifying urban vulnerability to terrorist incidents. Risk Analysis 27, 1411-1425 (2007).
Borden, K.A., Schmidtlein, M.C., Emrich, C.T., Piegorsch, W.W. and Cutter, S.L. Vulnerability of U.S. cities to environmental hazards. Journal of Homeland Security and Emergency Management 4 (2), Art. 5 (2007).
Wu, Y., Piegorsch, W.W., West, R.W., Tang, D., Petkewich, M.O., and Pan, W. Multiplicity-adjusted inferences in risk assessment: Benchmark analysis with continuous response data . Environmental and Ecological Statistics, 13, 125-141 (2006).