Deborah G. Mayo is Professor Emerita in the Department of Philosophy at Virginia Tech and is a visiting professor at the London School of Economics and Political Science: Center for the Philosophy of Natural and Social Science (CPNSS) . Her most recent book is Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (2018, CUP). She is the author of Error and the Growth of Experimental Knowledge (1996, Chicago) which won the 1998 Lakatos Prize awarded to the most outstanding contribution to the philosophy of science during the previous six years. She Directed the NEH Summer Seminar (1999) on Philosophy of Experiment: Induction, Reliability, and Error. She co-edited, with Aris Spanos, Error and Inference, Recent Exchanges on Experimental Reasoning, Reliability, and the Objectivity and Rationality of Science (2010, CUP). (In this volume, she is author or co-author of four chapters and six “exchanges” with the contributors A. Chalmers, A. Musgrave, P. Achinstein, J. Worrall, C. Glymour and L. Laudan.) Professor Mayo co-edited, with Rochelle Hollander, Acceptable Evidence: Science and Values in Risk Management (1991, Oxford). She co-founded, with G. W. Chatfield, the Fund for Experimental Reasoning, Reliability and Objectivity and Rationality (E.R.R.O.R) in 2006 which has co-sponsored 10 conferences, workshops and distinguished lecture series. She has published widely in the philosophy of science, statistics, and experimental inference and interdisciplinary works on evidence relevant for regulation and policy.
Aris Spanos is the Wilson E. Schmidt Professor of Economics at Virginia Tech. He has also taught at Birkbeck College (London University), the University of Cambridge, the University of California (Santa Barbara), and the University of Cyprus. Professor Spanos is the author of Probability Theory and Statistical Inference: Empirical Modeling with Observational Data (2019), Probability Theory and Statistical Inference (1999) and Statistical Foundations of Econometric Modeling (1986), all published by Cambridge University Press. Professor Spanos’s research has appeared in journals such as the Journal of Econometrics, Econometric Theory, Econometric Reviews, Statistical Methodology, Communications in Statistics (Theory and Methods), Philosophy of Science, Synthese and the British Journal for the Philosophy of Science. His research interests include the philosophy and methodology of statistical inference and modeling, foundational problems in statistics, statistical adequacy, misspecification testing and respecification, resampling and simulation techniques, macroeconometric modeling, and modeling speculative prices.
Joint Papers & Chapters (selected)
Spanos, A. and Mayo, D. G. (2015). “Error Statistical Modeling and Inference: Where Methodology Meets Ontology”. Synthese, 192(11), 3533-3555.
Mayo, D. G. and Spanos, A. (2011) “Error Statistics” in Philosophy of Statistics , Handbook of Philosophy of Science Volume 7 Philosophy of Statistics, (General editors: Dov M. Gabbay, Paul Thagard and John Woods; Volume eds. Prasanta S. Bandyopadhyay and Malcolm R. Forster.) Elsevier: 1-46.
Mayo, D. G. and Spanos, A. (2010). “Introduction and Background: Part I: Central Goals, Themes, and Questions; Part II The Error-Statistical Philosophy” in Error and Inference: Recent Exchanges on Experimental Reasoning, Reliability and the Objectivity and Rationality of Science (D Mayo and A. Spanos eds.), Cambridge: Cambridge University Press: 1-14, 15-27.
Mayo, D. and Spanos, A. (2008). “Risks to Health and Risks to Science: The Need for a Responsible ‘Bioevidential Scrutiny,'” Biological effects of low Level Exposures, Newsletter 14(3): 18-22.
Mayo, D. G. and Spanos, A. (2006). “Severe Testing as a Basic Concept in a Neyman-Pearson Philosophy of Induction,” British Journal of Philosophy of Science, 57: 323-357.
Mayo, D. and Spanos, A (2004). “Methodology in Practice: Statistical Misspecification Testing,” Philosophy of Science 71: 1007-1025.
D. G. Mayo Papers (selected): (See also publications page)
Mayo, D. G. (2016). “Don’t Throw out the Error Control Baby with the Bad Statistics Bathwater: A Commentary” on R. Wasserstein and N. Lazar: “The ASA’s Statement on P-values: Context, Process, and Purpose”, The American Statistician 70(2).
Mayo, D. G. (2014). “On the Birnbaum Argument for the Strong Likelihood Principle,” (with discussion) Statistical Science 29(2) pp. 227-239, 261-266.
Mayo, D. (2018). “Experimental Flukes and Statistical Modeling in the Higgs Discovery,” in Isabelle Peschard and Bas van Fraassen (eds.), The Experimental Side of Modeling in Minnesota Studies in the Philosophy of Science, University of Minnesota Press, 189-217.
Mayo, D.G. and Cox, D. R. (2006) “Frequentist Statistics as a Theory of Inductive Inference,” Optimality: The Second Erich L. Lehmann Symposium (ed. J. Rojo), Lecture Notes-Monograph series, Institute of Mathematical Statistics (IMS), Vol. 49: 77-97.
A. Spanos Papers (selected):
Spanos, A. (2010). “Is Frequentist Testing Vulnerable to the Base-Rate Fallacy?”, Philosophy of Science 77(4): 565-583.
Spanos, A. (2013). “Who Should Be Afraid of the Jeffreys-Lindley Paradox?”, Philosophy of Science 80 (1): 73-93.
Spanos, A. (2013). “A frequentist interpretation of probability for model-based inductive inference”, Synthese 190: 1555–1585.
Spanos, A. (2013). “Revisiting the Likelihoodist Evidential Account [Comment on ‘A Likelihood Paradigm for Clinical Trials’]” Journal of Statistical Theory and Practice 7: 187–195.
Spanos, A. (2018).” Mis-Specification Testing in Retrospect”, Journal of Economic Surveys 32(2): 541–577.