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Related Experiment Videos

The sampling distribution of d'

J Miller1

  • 1University of Otago, Dunedin, New Zealand. miller@otago.ac.nz

Perception & Psychophysics
|January 1, 1996
PubMed
Summary
This summary is machine-generated.

Computer tabulations reveal that sample estimated d

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Area of Science:

  • Psychology
  • Cognitive Science
  • Psychophysics

Background:

  • Signal detection theory (SDT) is a framework used to analyze the decisions made by observers when faced with uncertain stimuli.
  • The d' parameter in SDT quantifies an observer's sensitivity to a signal.
  • Estimating d' from sample data can be challenging due to the mathematical intractability of its distribution.

Purpose of the Study:

  • To investigate the properties of sample estimated d' distributions using computer simulations.
  • To identify biases and variances in estimated d' values under various conditions.
  • To evaluate the accuracy of standard confidence interval formulas for d' and explore alternative computation methods.

Main Methods:

  • Computer-based tabulation of the distribution of sample estimated d' values.

Related Experiment Videos

  • Analysis of how sample size, true d' value, and handling of undefined cases affect estimates.
  • Comparison of standard confidence interval formulas with direct computation for accuracy.

    • Main Results:

    • Sample estimated d' values are biased, with the bias direction and magnitude dependent on sample size and true d'.
    • The variance of estimated d' is influenced by the convention for undefined values and can deviate from standard approximations.
    • Standard confidence intervals for d' are accurate with sufficient trials (50-100), but direct computation offers better accuracy for smaller samples.

    Conclusions:

    • Computer simulations are valuable for understanding the complex distribution of estimated d'.
    • Researchers should be aware of the potential biases and variances in estimated d' and the impact of data handling conventions.
    • Direct computation methods provide more accurate confidence intervals for d', especially with limited data.