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Detection theory or signal detection theory is a means to measure the ability to differentiate between information-bearing patterns (called stimulus in living organisms, signal in machines) and random patterns that distract from the information (called noise, consisting of background stimuli and random activity of the detection machine and of the nervous system of the operator).
However, it also has important drawbacks. First, the threshold estimation is based only on p(yes), namely on "Hit" in Signal Detection Theory terminology. Second, and consequently, it is not bias free or criterion free. Third, the threshold is identified with the p(yes) = .5, which is just a conventional and arbitrary choice.
Detection performance loss is less likely to occur in cases where the target signal exhibits a high saliency. For example, a radar operator would be unlikely to miss a rare target at the end of a watch if it were a large bright flashing signal, but might miss a small dim signal.
Signal detection theory (SDT) involves a bias and reduces ability to distinguish tools from weapons after a Black prime even in situations when race was incidental (nondiagnostic). The only cue the participants were obligated to attend to was the presence of a weapon or non-weapon. [ 8 ]
Signal detection theory has been applied to recognition memory as a method of estimating the effect of the application of these internal criteria, referred to as bias. Critical to the dual process model is the assumption that recognition memory reflects a signal detection process in which old and new items each have a distinct distribution ...
Signal-detection theory assumed a preeminent position in the field of recognition memory in large part because its predictions about the shape of the ROC were almost always shown to be more accurate than the predictions of the intuitively plausible high-threshold model. [5]
The sensitivity index or discriminability index or detectability index is a dimensionless statistic used in signal detection theory. A higher index indicates that the signal can be more readily detected.
The sensitivity index or d′ (pronounced "dee-prime") is a statistic used in signal detection theory. It provides the separation between the means of the signal and the noise distributions, compared against the standard deviation of the noise distribution.