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Modeling visual search using three-parameter probability functions in a hierarchical Bayesian framework


Lin, Y and Heinke, D and Humphreys, GW, Modeling visual search using three-parameter probability functions in a hierarchical Bayesian framework, Attention, Perception, & Psychophysics, 77, (3) pp. 985-1010. ISSN 1943-3921 (2015) [Refereed Article]

Copyright Statement

Copyright 2015 The Psychonomic Society, Inc.

DOI: doi:10.3758/s13414-014-0825-x


In this study, we applied Bayesian-based distributional analyses to examine the shapes of response time (RT) distributions in three visual search paradigms, which varied in task difficulty. In further analyses we investigated two common observations in visual search-the effects of display size and of variations in search efficiency across different task conditions-following a design that had been used in previous studies (Palmer, Horowitz, Torralba, & Wolfe, Journal of Experimental Psychology: Human Perception and Performance, 37, 58-71, 2011; Wolfe, Palmer, & Horowitz, Vision Research, 50, 1304-1311, 2010) in which parameters of the response distributions were measured. Our study showed that the distributional parameters in an experimental condition can be reliably estimated by moderate sample sizes when Monte Carlo simulation techniques are applied. More importantly, by analyzing trial RTs, we were able to extract paradigm-dependent shape changes in the RT distributions that could be accounted for by using the EZ2 diffusion model. The study showed that Bayesian-based RT distribution analyses can provide an important means to investigate the underlying cognitive processes in search, including stimulus grouping and the bottom-up guidance of attention.

Item Details

Item Type:Refereed Article
Keywords:Hierarchical bayesian model, visual search
Research Division:Psychology
Research Group:Applied and developmental psychology
Research Field:Psychological methodology, design and analysis
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in psychology
UTAS Author:Lin, Y (Dr Yingru Lin)
ID Code:102964
Year Published:2015
Web of Science® Times Cited:2
Deposited By:Psychology
Deposited On:2015-09-13
Last Modified:2017-10-31

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