Fri, 04 Jul 2008 23:41:00 BST CiteULike: acslab's group http://www.citeulike.org/user/acslab/tag/group CiteULike.org en-gb Copyright © 2004-2008 citeulike.org http://www.citeulike.org/user/acslab/article/2714435 <i>Journal of Experimental Psychology: Applied, Vol. 6, No. 2. (1 June 2000), pp. 130-147.</i><br /><br />The average probability estimate of J > 1 judges is generally better than its components. Two studies test 3 predictions regarding averaging that follow from theorems based on a cognitive model of the judges and idealizations of the judgment situation. Prediction 1 is that the average of conditionally pairwise independent estimates will be highly diagnostic, and Prediction 2 is that the average of dependent estimates (differing only by independent error terms) may be well calibrated. Prediction 3 contrasts between- and within-subject averaging. Results demonstrate the predictions' robustness by showing the extent to which they hold as the information conditions depart from the ideal and as J increases. Practical consequences are that (a) substantial improvement can be obtained with as few as 2–6 judges and (b) the decision maker can estimate the nature of the expected improvement by considering the information conditions. The Effects of Averaging Subjective Probability Estimates Between and Within Judges Dan Ariely Wing Au Randall Bender David Budescu Christiane Dietz Hongbin Gu Thomas Wallsten Gal Zauberman doi:10.1037/1076-898X.6.2.130 Journal of Experimental Psychology: Applied, Vol. 6, No. 2. (1 June 2000), pp. 130-147. 2008-04-24T21:40:37-00:00 2000 Journal of Experimental Psychology: Applied 6 2 130 147 confidence-judgment group subjective-probability http://www.citeulike.org/user/acslab/article/2714411 <i>Acta Psychologica, Vol. 104, No. 3. (June 2000), pp. 371-398.</i><br /><br />We investigate the case of a single decision maker (DM) who obtains probabilistic forecasts regarding the occurrence of a unique target event from J distinct, symmetric, and equally diagnostic expert advisors (judges). The paper begins with a mathematical model of DM's aggregation process of expert opinions, in which confidence in the final aggregate is shown to be inversely related to its perceived variance. As such, confidence is expected to vary as a function of factors such as the number of experts, the total number of cues, the fraction of cues available to each expert, the level of inter-expert overlap in information, and the range of experts' opinions. In the second part of the paper, we present results from two experiments that support the main (ordinal) predictions of the model. Confidence in aggregation of expert opinions David Budescu Adrian Rantilla doi:10.1016/S0001-6918(00)00037-8 Acta Psychologica, Vol. 104, No. 3. (June 2000), pp. 371-398. 2008-04-24T21:35:56-00:00 2000 Acta Psychologica 104 3 371 398 confidence-judgment group http://www.citeulike.org/user/acslab/article/2714401 <i>Organizational Behavior and Human Decision Processes, Vol. 90, No. 1. (January 2003), pp. 178-194.</i><br /><br />We investigate the case of a Decision Maker (DM) who obtains probabilistic forecasts regarding the occurrence of a target event from J distinct, asymmetric advisors. In this context, asymmetry is induced by manipulating: (1) amount of information (number of diagnostic cues) available to each advisor and (2) quality (accuracy) of advisors' previous forecasts. Empirical results from two experiments indicate that the DM's final estimate can be described as a weighted average of advisor forecasts, where the weights are sensitive to both sources of asymmetry. This work extends the model derived by Budescu and Rantilla (2000) for the DMs confidence in the aggregate to accommodate advisor asymmetry. As in the symmetric case, the DM's confidence in the weighted average of the forecasts is a function of the number of judges, the total number of cues, the (inferred) inter-judge correlation, and the level of inter-judge overlap in information. The extended model predicts that confidence increases as a function of asymmetry among judges. Empirical results support the main (ordinal) predictions of the model, including the predicted effect of inter-judge asymmetry. The effects of asymmetry among advisors on the aggregation of their opinions David Budescu Adrian Rantilla Hsiu-Ting Yu Tzur Karelitz doi:10.1016/S0749-5978(02)00516-2 Organizational Behavior and Human Decision Processes, Vol. 90, No. 1. (January 2003), pp. 178-194. 2008-04-24T21:31:01-00:00 2003 Organizational Behavior and Human Decision Processes 90 1 178 194 confidence-judgment group uncertainty http://www.citeulike.org/user/acslab/article/306015 <i>Trends in Cognitive Sciences, Vol. 9, No. 9. (September 2005), pp. 424-430.</i><br /><br />Computational models of human collective behavior offer promise in providing quantitative and empirically verifiable accounts of how individual decisions lead to the emergence of group-level organizations. Agent-based models (ABMs) describe interactions among individual agents and their environment, and provide a process-oriented alternative to descriptive mathematical models. Recent ABMs provide compelling accounts of group pattern formation, contagion and cooperation, and can be used to predict, manipulate and improve upon collective behavior. ABMs overcome an assumption that underlies much of cognitive science - that the individual is the crucial unit of cognition. The alternative advocated here is that individuals participate in collective organizations that they might not understand or even perceive, and that these organizations affect and are affected by individual behavior. Computational models of collective behavior Robert Goldstone Marco Janssen doi:10.1016/j.tics.2005.07.009 Trends in Cognitive Sciences, Vol. 9, No. 9. (September 2005), pp. 424-430. 2005-08-29T10:04:06-00:00 2005 Trends in Cognitive Sciences 9 9 424 430 group models