Description Usage Arguments Details Value Author(s) References See Also Examples
Calulate d' for samedifferent paradigm either assuming a differencing strategy or independent observations
1  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 zscores 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 samedifferent
paradigm. With Independent Observations, d' can be calculated
either from the H
and FA
rates, from the difference of
zscores 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
1 2 3 4 
[1] 1.950605
[1] 1.954916
[1] 1.954916
[1] 1.954916
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