ERROR06 Participants

 

SPECIAL INVITED SPEAKERS

 

Dr. Peter Achinstein

Dept of Philosophy, Johns Hopkins University

pachins1@jhem.jhu.edu

Mill's Sins: Correcting Some Errors About Mill

Peter Achinstein is founder and director of the Johns Hopkins Center for History and Philosophy of Science.  He is the author of the books Concepts of Science (1968), Law and Explanation (1971), The Nature of Explanation (1983), Particles and Waves (1991) which received the Lakatos Award in Philosophy of Science, and The Book of Evidence (2001).  He directed two NEH Summer Seminars and has held Guggenheim, NEH, and NSF fellowships.

Dr. Alan Chalmers

Flinders University of South Australia

chal0034@flinders.edu.au

Theory Testing and the New Experimentalism

 

Dr. Chalmers is the author of What Is This Thing Called Science? (first published in 1976 and now in its third edition) and Science and Its Fabrication (1990).

 

Sir David Cox

Dept of Statistics, University of Oxford

david.cox@nuf.ox.ac.uk

Principles of Frequentist Statistics

 

Sir Cox has made major contributions to statistical theory, method, and applications. Among his many recognitions, he has received the Guy Medal in Silver and Gold from the Royal Statistical Society, the Weldon Memorial Prize, the Kettering Prize and Gold Medal for Cancer Research, and was knighted in 1975. His books include The Foundations of Statistical Inference, with G. A. Barnard (1961), Statistical Analysis of Series of Events, with P.A.W. Lewis (1966), Theoretical Statistics, with D. V. Hinkley (1974), Applied Statistics with E J Snell (1981); Inference and asymptotics with O. E. Barndorff- Nielsen (1994); and Theory of the Design of Experiments, with N. Reid (2000). He edited the journal Biometrika from 1966 to 1991.

 

Dr. Clark Glymour

Dept of Philosophy, Carnegie Mellon University

cg09@andrew.cmu.edu

Error: Its Measurement and Use in Reliable Modeling: Indian Chief Experiment

 

Clark Glymour is Alumni University Professor at Carnegie Mellon University, Senior Research Scientist at the Florida Institute for Human and Machine Cognition, and adjunct Professor of History and Philosophy of Science at the University of Pittsburgh. His books include Theory and Evidence (1980), Foundations of Space-Time Theories, with J. Earman (1986), Examining Holistic Medicine, with D. Stalker (1986). Discovering Causal Structure, with R. Scheines, P. Spirtes, and K. Kelly (1987), Causation, Prediction, and Search, with P. Spirtes and R. Scheines (1993, 2001), Android Epistemology (2002) and Thinking About Android Epistemology (2006), both with P. Hayes and K. Ford, and Bayes Nets and Graphical Causal Models in Psychology (2001). He has been a Guggenheim Fellow, a Fellow of the Center for Advanced Studies in the Behavioral Sciences, and a Romanell Phi Beta Kappa lecturer.

Dr. Henry Kyburg

Depts of Philosophy, Computer Science, University of Rochester

hkyburg@ihmc.us

Corrigible Acceptance and Incorrigible Conditioning

 

Dr. Kyburg is also a Senior Research Scientist and Pace Eminent Scholar at the Institute for Human and Machine Cognition (West Florida). His books include Probability and the Logic of Rational Belief (1961), Probability and Inductive Logic (1970), The Logical Foundations of Statistical Inference (1974), Theory and Measurement (1984), Science and Reason (1990), and Uncertain Inference, with Choh Man Teng (2001). He was Director of an NEH Summer Seminar and has held fellowships from NSF and other agencies.

 

Dr. Larry Laudan
Senior Investigator, Institute for Philosophical Research, National Autonomous University of Mexico
llaudan@larrylaudan.com

The Defendant's Burden: the Onus Probandi and the Anomaly of Affirmative Defenses

 

Dr. Laudan is founder of the journal Studies in History and Philosophy of Science, and served as its editor from 1969 to 1974. He is author of Progress and Its Problems (1977), Science and Hypothesis (1981), Science and Values (1984), Science and Relativism (1991), Beyond Positivism and Relativism (1996), and Truth, Error and Criminal Law (2006). He was founding chair of History and Philosophy of Science at the University of Pittsburgh and Director of the Philosophy of Science Center there. He was divisional President of the American Philosophical Association from 1994-95.  He was a Fulbright Fellow at Konstanz (1980) and Vienna (1972) and Member of the School of Social Sciences at the Institute for Advanced Study (1995). 

 

Dr. Deborah Mayo

Depts of Philosophy & Economics; Virginia Tech

mayod@vt.edu

Severe Tests, Error Statistics, and the Growth of Theoretical Knowledge

 

Dr. Mayo is the author of Error and the Growth of Experimental Knowledge which received the 1998 Lakatos Prize award, was a Director of a NEH Summer Seminar on induction and experimental inference, and has held fellowships from NEH and NSF.

 

Dr. Alan Musgrave

Dept of Philosophy, University of Otago, New Zealand

alan.musgrave@stonebow.otago.ac.nz

Critical Rationalism and Severe Testing—place holder title

 

He co-edited with Imre Lakatos the celebrated collection Criticism and the Growth of Knowledge, and has authored the books Common Sense, Science, and Scepticism (1993) and Essays on Realism and Rationalism (1999).

 

Dr. Aris Spanos

Dept of Economics, Virginia Tech

aris@vt.edu

Statistical Induction, Severe Testing and Model Validation

 

Wilson Schmidt Professor and Chair of the Department of Economics, is the author of Statistical Foundations of Econometric Modelling (1986) and Probability Theory and Statistical Inference: Econometric Modeling with Observational Data (1999).

 

Professor John Worrall
Dept. of Philosophy, Logic and Scientific Method, London School of Economics
j.worrall@lse.ac.uk
Error, Tests and Theory-Confirmation in Science


Dr. Worrall is Professor of Philosophy of Science at the LSE. He is the author of numerous articles mostly on issues concerning theory-change in science; and also, more recently, on issues in the methodology of medicine. He served as editor of The British Journal for Philosophy of Science from 1974 to 1983 and is the Head of the Committee for the prestigious Lakatos Award. He is currently completing a book called Reason in 'Revolution': A Study of Theory-Change in Science (Oxford University Press, 2007).

 

WORKSHOP PAPERS

 

Dr. Thomas Bartz-Beielstein

Dept. of Computer Science, University of Dortmund, Germany

thomas.bartz-beielstein@udo.edu

NPT* in Evolutionary Computing

Workshop 5: Error, Epidemiology and Evolutionary Computation

 

Dr. Rodolfo de Cristofaro

Dept. of Statistics, University of Florence, Italy

decrist@ds.unifi.it

Foundations of the 'Objective Bayesian Analysis'

Workshop 3: Error, Probability and Logic

 

Dr. Brian Dennis

Fish and Wildlife Resources; University of Idaho

brian@uidaho.edu

Keeping the faith: how prior beliefs can become data resistant

Workshop 2: Error and Ecology

 

Frederick Eberhardt

Dept of Philosophy, Carnegie Mellon Univerity

fde@andrew.cmu.edu

Conflicts in Sequences of Experiments

Workshop 4: Error, Causal Discovery and Model Selection

 

Dr. Malcolm Forster

Dept of Philosophy, University of Wisconsin-Madison

mforster@wisc.edu

Counterexamples to a Likelihood Theory of Evidence

Workshop 4: Error, Causal Discovery and Model Selection

 

Dr. Pamela Jo Johnson

University of Minnesota, State Health Access Data Assistance Center & Minnesota Population Center

johns245@umn.edu

Specification and Confounding Errors When Using Non-Experimental, Observational Data to Make Causal Inferences

Workshop 5: Error, Epidemiology and Evolutionary Computation

 

Dr. Thomas Kepler

Division Chief, Computational Biology
Department of Biostatistics and Bioinformatics, Duke University

keple003@mc.duke.edu

Whither Statistics on Biology's Wings?

Workshop 5: Error, Epidemiology and Evolutionary Computation

 

Dr. Subash Lele

Dept of Mathematical and Statistical Sciences, University of Alberta

slele@stat.ualberta.ca

On quantifying evidence in the presence of nuisance parameters: Evidence functions and their applications in ecology

Workshop 2: Error and Ecology

 

Dr. Wendy Parker

Dept of Science Studies, University of California San Diego

wparker@ucsd.edu

Computer Simulation through an Error-Statistical Lens

Workshop 1: Error and Evidence: Methodology and Theory Appraisal

 

Dr. John Roberts

Dept of Philosophy; University of North Carolina, Chapel Hill

jtrosap@email.unc.edu

Coping With Severe Test Anxiety: Problems and Prospects for an Error-Statistical Approach to the Testing of High-Level Theories

Workshop 1: Error and Evidence: Methodology and Theory Appraisal

 

Dr. Kent Staley

Dept of Philosophy; Saint Louis University

staleykw@slu.edu

Error-statistical Theory Assessment and Alternative Hypothesis Problems: A Role for Judgments of Plausibility?

Workshop 1: Error and Evidence: Methodology and Theory Appraisal

 

Dr. Mark Taper

Department of Ecology; Montana State University

taper@rapid.msu.montana.edu

Model Structural Adequacy

Workshop 2: Error and Ecology

 

Dr. Andrew Ward

University of Minnesota, State Health Access Data Assistance Center & Minnesota Population Center

ward0230@umn.edu; johns245@umn.edu

Specification and Confounding Errors When Using Non-Experimental, Observational Data to Make Causal Inferences

Workshop 5: Error, Epidemiology and Evolutionary Computation

 

Dr. Greg Wheeler

Department of Computer Science, Universidade Nova de Lisboa

greg@di.fct.unl.pt

Compounding Doubts

Workshop 3: Error, Probability and Logic

 

Dr. Jon Williamson

Dept of Philosophy, University of Kent

j.williamson@kent.ac.uk

Inductive Influence

Workshop 3: Error, Probability and Logic

 

Dr. Jiji Zhang

Dept of Philosophy, Carnegie Mellon University

jiji@andrew.cmu.edu

Seeking Truth and Avoiding Error: What Can We Hope Causal Inference Procedures to Achieve?

Workshop 4: Error, Causal Discovery and Model Selection

 

POSTERS

 

Brooke Abounader

IHPST , University of Toronto

The Importance of Error in Learning from Scientific Models

 

Emrah Aktunc

Depts of STS and Philosophy, Virginia Tech

maktunc@vt.edu

The Tacking Paradox: A Critique of Bayesian Treatments and an Error-Statistical Proposal for Its Solution

 

Dr. John Byrd

Central Identification Laboratory, Joint POW/MIA Accounting Command

John.Byrd@JPAC.PACOM.MIL

The Role of E.R.R.O.R. in the Forensic Identification of Human Remains

 

Andre Crawford

Dept. of Economics, Virginia Tech

andrec@vt.edu

Evaluating Economics: What have we learnt from Empirical Modeling

 

Dr. Jeffery Downard

Dept of Philosophy, Northern Arizona University

Jeffrey.Downard@nau.edu

Inductive Forms of Inference in Law

 

Dr. Damien Fennell

Centre for Philosophy of Natural and Social Science,

London School of Economics

D.J.Fennell@lse.ac.uk

The Error Term and its Interpretation in Structural Models in Econometrics

 

Ulrich Frey

University of Braunschweig, Germany

u.frey@tu-bs.de

Recurring scientific errors and their connection to evolutionary cognitive psychology

 

Dr. Clark Glymour

Dept of Philosophy, Carnegie Mellon University

Senior Research Scientist at the Institute for Human and Machine Cognition (West Florida)

cg09@andrew.cmu.edu

Rocks, Genes, Fire and Lead: Avoiding Testing

 

Dr. Galina Granek

Dept of Philosophy, University of Haifa

granek@research.haifa.ac.il

Scanning Tunneling Microscope (STM): an ancillary error that led to a gestalt switch

 

Christina Kayrouz

Dept of Philosophy, Western Kentucky University

"Debunking" the Global Warming Myth: Error and the Experimental Process in Climatology

 

Dr. Tom Koehnle

Dept Of Neuroscience, University of Pittsburg

koehnle@bns.pitt.edu

Using Monte Carlo Simulations to Evaluate the Design and Analysis of Experiments: The Case of Pseudoreplication.

 

Dr. Jefferey Schank

Dept of Psychology, Animal Behavior Graduate Group, University of California Davis

jcschank@ucdavis.edu

Using Monte Carlo Simulations to Evaluate the Design and Analysis of Experiments: The Case of Pseudoreplication.

 

Dr. Aris Spanos & Students

Dept. of Economics, Virginia Tech

aris@vt.edu

Severity Excel program

 

Jane Mazzaggatti

UNISYS Corporation; Blue Bell, PA

Jane.Mazzagatti@unisys.com

The Potential for Recognizing Errors in a Dataset Using a Computer Memory Resident Data Structure Based on the Phaneron of C.S. Peirce

 

Dr. Avital Pilpel

Dept. of Philosophy

University of Haifa

Avital.Pilpel@gmail.com

The Role of Theoretical Rationality in Dealing with Error

 

Dr. David Rudge

Department of Biological Sciences & The Mallinson Institute for Science Education, Western Michigan University

david.rudge@wmich.edu

Kettlewell from an Error Statistician's Point of View

 

Dr. Bertold Schweitzer

Dept of Philosophy, University of Osnabruck

Bertold.schweitzer@uni-osnabrueck.de

bschweit@uos.de

How Something Works Is Most Easily found Out If It Doesn't Work

 

Dr. Leonard Smith

Oxford Centre for Industrial and Applied Mathematics, Oxford University

lenny@maths.ox.ac.uk

Using Error(s) to Improve and Interpret Nonlinear Models of Dynamic Systems

 

Roger Stanev

University of British Columbia

rstanev@interchange.ubc.ca

P-value Fallacy, Bayes Factor, Error Probabilities and Experimental Learning

 

Dr. Eric Walker

NASA Langley Research Center

eric.l.walker@nasa.gov

Learning from Error in the Calibration and Validation of Mechanistic Models

 

Program Committee

 

Jean Miller

Depts of Philosophy & STS

Virginia Tech

Jemille6@vt.edu