dprime.SD | R Documentation |
Calulate d'
for same-different paradigm either
assuming a differencing strategy or independent observations
dprime.SD(H, FA, zdiff, Pcmax, method = "diff")
H |
numeric in [0, 1] corresponding to Hit rate |
FA |
numeric in [0, 1] corresponding to False alarm rate |
zdiff |
numeric. Difference of z-scores for Hit and False Alarm rates ( only valid for method "IO") |
Pcmax |
numeric in [0, 1]. Proportion correct for an unbiased observer,
|
method |
character. Specifies the model to describe the observer's criterion for dividing up the decision space, must be either "diff" for a differencing strategy (the default) or "IO" for independent observations. |
Two different strategies have been described for how the
observer partitions the decision space in the same-different
paradigm. With Independent Observations, d'
can be calculated
either from the H
and FA
rates, from the difference of
z-scores or from the probability correct of an unbiased observer.
Only one of these three choices should be specified in the arguments.
For the differencing strategy, only the first of these choices is valid.
Returns the value of d'
Kenneth Knoblauch
MacMillan, N. A. and Creeman, C. D. (1991) Detection Theory: A User's Guide Cambridge University Press
Green, D. M. and Swets, J. A. (1966) Signal Detection Theory and Psychophysics Robert E. Krieger Publishing Company
dprime.mAFC
, dprime.ABX
,
dprime.oddity
dprime.SD(H = 0.642, F = 0.3)
dprime.SD(H = 0.75, F = 0.3, method = "IO")
dprime.SD(zdiff = qnorm(0.75) - qnorm(0.3), method = "IO")
dprime.SD(Pcmax = pnorm( (qnorm(0.75) - qnorm(0.3))/2 ), method = "IO")
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