The statistical analysis of concurrent detection ratings

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Abstract
The concurrent detection task is a powerful method for assessing interactions in the processing of two sensory signals. On each trial, a stimulus is presented that is composed of one, both, or neither signal, and the observer makes a detection rating for each stimulus. A classical bivariate signal-detection analysis applies to these data, but is limited by its inability to differentiate certain types of sensory interactions from more cognitive components, and by the lack of an associated testing procedure. The present paper presents an alternative analysis, based on the contingency table of sensory ratings. Six classes of effect can be distinguished and tested: (1) simple response bias, (2) detection of the two signals, (3) interference of each signal on the response to the other signal, (4) sensory and response correlation, (5) bivariate response biases, and (6) higher order association. Complete computational detail is provided.