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  Efficient Adaptive Sampling of the Psychometric Function by Maximizing Information Gain

Tanner, T., Hill, N., Rasmussen, C., & Wichmann, F. (2005). Efficient Adaptive Sampling of the Psychometric Function by Maximizing Information Gain. Poster presented at 8th Tübinger Wahrnehmungskonferenz (TWK 2005), Tübingen, Germany.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-D643-B Version Permalink: http://hdl.handle.net/21.11116/0000-0004-D6FA-1
Genre: Poster

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 Creators:
Tanner, TG1, 2, Author              
Hill, NJ2, 3, Author              
Rasmussen, CE2, 3, Author              
Wichmann, FA2, 3, Author              
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              
3Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              

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 Abstract: A psychometric function can be described by its shape and four parameters: position or threshold, slope or width, false alarm rate or chance level, and miss or lapse rate. Depending on the parameters of interest some points on the psychometric function may be more informative than others. Adaptive methods attempt to place trials on the most informative points based on the data collected in previous trials. We introduce a new adaptive bayesian psychometric method which collects data for any set of parameters with high efficency. It places trials by minimizing the expected entropy [1] of the posterior pdf over a set of possible stimuli. In contrast to most other adaptive methods it is neither limited to threshold measurement nor to forced-choice designs. Nuisance parameters can be included in the estimation and lead to less biased estimates. The method supports block designs which do not harm the performance when a sufficient number of trials are performed. Block designs are useful for control of response bias and short term performance shifts such as adaptation. We present the results of evaluations of the method by computer simulations and experiments with human observers. In the simulations we investigated the role of parametric assumptions, the quality of different point estimates, the effect of dynamic termination criteria and many other settings. [1] Kontsevich, L.L. and Tyler, C.W. (1999): Bayesian adaptive estimation of psychometric slope and threshold. Vis. Res. 39 (16), 2729-2737.

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 Dates: 2005-02
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 3256
 Degree: -

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Title: 8th Tübinger Wahrnehmungskonferenz (TWK 2005)
Place of Event: Tübingen, Germany
Start-/End Date: 2005-02-25 - 2005-02-27

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Title: 8th Tübingen Perception Conference: TWK 2005
Source Genre: Proceedings
 Creator(s):
Bülthoff, HH1, Editor            
Mallot, HA, Editor            
Ulrich, R, Editor
Wichmann, FA1, Editor            
Affiliations:
1 Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794            
Publ. Info: Kirchentellinsfurt, Germany : Knirsch
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 109 Identifier: ISBN: 3-927091-70-7