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Parameter estimates for a signal detection study

Source: R/statpsych3.R
signal.Rd

Computes the hit rate, false alarm rate, d-prime, threshold, and bias for one participant (observer) in a Yes/No signal detection study. An equal-variance Gausian model is assumed. The parameter estimates are computed after adding .5 to the number of "Yes" responses in each condtion (the signal and noise conditions) and adding 1 to the number of signal trials and to the number of noise trails. In memory recognition studies, the observer is first presented with set of words or images to study, and is later presented with another set of words or images where some items are from the first list (old items) and some items are new items.

Usage

signal(f1, f2, n1, n2)

Arguments

f1

number of "Yes" responses in the stimulus (old item) trials

f2

number of "Yes" responses in the noise (new item) trials

n1

number of stimulus (or old item) trials

n2

number of noise (or new item) trials

Value

Returns a 1-row matrix. The columns are:

  • HR - estimate of hit rate

  • FAR - estimate of false alarm rate

  • d-prime - estimate of d-prime

  • Threshold - estimate of threshold (criterion)

  • Bias - estimate of threshold minus d-prime/2

References

Wickens TD (2002). Elementary Signal Detection Theory. Oxford.

Examples

signal(82, 46, 100, 100)
#>         HR      FAR  d-prime  Threshold       Bias
#>  0.8168317 0.460396 1.002793 0.09943603 -0.4019603

# Should return:
#         HR      FAR  d-prime  Threshold       Bias
#  0.8168317 0.460396 1.002793 0.09943603 -0.4019603