Participant recruitment methods and statistical reasoning performance Gary L. Brase University of Missouri–Columbia, Columbia, MI, USA Laurence Fiddick ESRC Centre for Economic Learning and Social Evolution, and James Cook University, Townsville, Queensland, Australia Clare Harries University College London, London, UK Optimal Bayesian reasoning performance has reportedly been elusive, and a variety of explanations have been suggested for this situation. In a series of experiments, it is demonstrated that these diffi- culties with replication can be accounted for by differences in participant-sampling methodologies. Specifically, the best performances are obtained with students from top-tier, national universities who were paid for their participation. Performance drops significantly as these conditions are altered regarding inducements (e.g., using unpaid participants) or participant source (e.g., using par- ticipants from a second-tier, regional university). Honours-programme undergraduates do better than regular undergraduates within the same university, paid participation creates superior performance, and top-tier university students do better than students from lower ranked universities. Pictorial representations (supplementing problem text) usually have a slight facilitative effect across these participant manipulations. These results indicate that studies should take account of these methodo- logical details and focus more on relative levels of performance rather than absolute performance. One of the best known Bayesian reasoning tasks is the medical diagnosis problem, which originally was in the following form: If a test to detect a disease whose prevalence is 1/1,000 has a false positive rate of 5%, what is the chance that a person found to have a positive result actually has the disease, assuming that you know nothing about the person’s symptoms or signs?___% This original version was correctly answered by only 18% of medical students and doctors, which seemed to be uniformly agreed upon as poor per- formance (Casscells, Schoenberger, & Graboys, 1978); the correct posterior probability for this Correspondence should be addressed to Gary L. Brase, Department of Psychological Sciences, 210 McAlester Hall, University of Missouri– Columbia, Columbia, Missouri, 65211, USA. Email: braseg@missouri.edu The authors would like to thank the University of Sunderland and the ESRC for funding that supported Experiment 4, and Kimberly Sapp and Rebecca Miller for assistance in collecting some portions of the data. We also thank Sandra Brase and Mike Oaksford for advice and support regarding this research. # 2006 The Experimental Psychology Society 965 http://www.psypress.com/qjep DOI:10.1080/02724980543000132 THE QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY 2006, 59 (5), 965–976