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Peter Killeen

Peter Killeen

Professor, Psychology

Arizona State University
PO BOX 871104
Tempe, AZ 85287-1104


  • Professor, Psychology


Killeen studies behavioral decision theory, statistical inference, and information theory. He views his role as a consultant on theoretical or technical issues, rather than a content matter or interface specialist. He is eager to analyze real decision issues within these traditional frameworks and determine how to adapt them to concrete demands.

Journal Articles


Sanabria, F. and P. R. Killeen. 2007. Better statistics for better decisions: Rejecting null hypotheses statistical tests in favor of replication statistics. Psychology in Schools 44(5):471-481.


Killeen, P. R. 2006. Beyond statistical inference: A decision theory for science. Psychonomic Bulletin & Review 13(4):549-562. (link )

Killeen, P. R. 2006. The problem with Bayes. Psychological Science 17(7):643-644.


Killeen, P. R. 2005. Replicability, confidence, and priors. Psychological Science 16(12):1009-1012.

Killeen, P. R. 2005. An alternative to null-hypothesis significance tests. Psychological Science 16(5):345-353.

Sanabria, F. and P. R. Killeen. 2005. Freud meets Skinner: Hyperbolic curves, elliptical theories, and Ainslie interests. Behavioral and Brain Sciences 28(5):660-661.

Book Chapters


Killeen, P. R. 2007. Replication statistics. Pp. 103-124 In: Osborne, J. W. ed., Best Practices in Quantitative Methods. Sage Publications. Thousand Oaks, CA.



Killeen, P. R. 2008. The law of affect. Paper presented at the South American Psychological Association, Bogota, Colombia.

Killeen, P. R. 2008. The mother of all discount functions. Paper presented at the Association for Psychological Science.


Killeen, P. R. 2007. The 3 Ms of analysis: Minding, mining, and modeling our data. Keynote Address February 3, 2007 at the Winter Conference on Animal Learning and Behavior, Winter Park, CO.


Killeen, P. R. 2006. A decision theory for scientific inference. Presented at Washington University.

Killeen, P. R. 2006. Retroduction ± e: Parsimony, goodness of fit, & validity generalization. Presented at Workshop Model Comparison, Syracuse, NY.