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Choice, Decision, and Measurement

Download or Read eBook Choice, Decision, and Measurement PDF written by A.A.J. Marley and published by Routledge. This book was released on 2019-05-23 with total page 489 pages. Available in PDF, EPUB and Kindle.
Choice, Decision, and Measurement
Author :
Publisher : Routledge
Total Pages : 489
Release :
ISBN-10 : 9781317729419
ISBN-13 : 1317729412
Rating : 4/5 (19 Downloads)

Book Synopsis Choice, Decision, and Measurement by : A.A.J. Marley

Book excerpt: This volume is the result of a conference held at the University of California, Irvine, on the topics that provide its title -- choice, decision, and measurement. The conference was planned, and the volume prepared, in honor of Professor R. Duncan Luce on his 70th birthday. Following a short autobiographical statement by Luce, the volume is organized into four topics, to each of which Luce has made significant contributions. The book provides an overview of current issues in each area and presents some of the best recent theoretical and empirical work. Personal reflections on Luce and his work begin each section. These reflections were written by outstanding senior researchers: Peter Fishburn (Preference and Decision Making), Patrick Suppes (Measurement Theory and Axiomatic Systems), William J. McGill (Psychophysics and Reaction Time), and W.K. Estes (Choice, Identification and Categorization). The first section presents recent theoretical and empirical work on descriptive models of decision making, and theoretical results on general probabilistic models of choice and ranking. Luce's recent theoretical and empirical work on rank- and sign-dependent utility theory is important in many of these contributions. The second section presents results from psychophysics, probabilistic measurement, aggregation of expert opinion, and test theory. The third section presents various process oriented models, with supportive data, for tasks such as redundant signal detection, forced choice, and absolute identification. The final section contains theory and data on categorization and attention, and general theoretical results for developing and testing models in these domains.


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