December 2006
Volume 6, Issue 13
Free
OSA Fall Vision Meeting Abstract  |   December 2006
Signal detection rating models underlying the uncertainty paradigm
Author Affiliations
  • Lynn A. Olzak
    Department of Psychology, Miami University of Ohio, Oxford, OHUSA
  • Jordan R. Wagge
    Psychology, Miami University of Ohio
  • Robin D. Thomas
    Psychology, Miami University of Ohio
Journal of Vision December 2006, Vol.6, 58. doi:10.1167/6.13.58
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      Lynn A. Olzak, Jordan R. Wagge, Robin D. Thomas; Signal detection rating models underlying the uncertainty paradigm. Journal of Vision 2006;6(13):58. doi: 10.1167/6.13.58.

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Abstract

In previous work, we have shown that violating certain assumptions underlying multidimensional decision models has little effect on the performance ratio in an uncertainty paradigm when modeled as a yes/no task. In certainty conditions, the observer knows in advance which of two components or dimensions will carry a signal to be discriminated. In uncertainty conditions, the relevant dimension or component is unknown. The performance ratio is the ratio of d' values in uncertainty and certainty conditions. However, many absolute d' values could lead to the same performance ratio. Here, we extend the analysis to a rating task and directly examine d' in the uncertainty condition. We varied the relative saliency of each potential cue by varying the relative mean and variance values defining each underlying distribution, violated assumptions of equal variance, etc. Despite large changes in these values, d' values based on 10000 simulated trials varied over a range less than 0.1 d' until. We conclude from these and our performance ratio results that the paradigm is very robust with respect to underlying assumptions, and that violations of them do little to skew results.

Olzak, L. A. Wagge, J. R. Thomas, R. D. (2006). Signal detection rating models underlying the uncertainty paradigm [Abstract]. Journal of Vision, 6(13):58, 58a, http://journalofvision.org/6/13/58/, doi:10.1167/6.13.58. [CrossRef]
Footnotes
 Supported by NIH grant EY13953 to LAO.
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