Signal detection theory analyses of semantic priming in word recognition.

Word recognition, semantic priming, and cognitive impenetrability research have used signal detection theory (SDT) measures to separate perceptual and postperceptual processes. In the D. Norris (1986) checking model and model simulation (D. Norris, 1995), priming alters only postperceptual word decision criteria: Stimulus-related priming reduces uncertainty, increasing sensitivity; stimulus-unrelated priming increases false alarms more than hits, reducing sensitivity. This work is cited as strong evidence that criterion changes can alter perceptual sensitivity and that SDT is inappropriate for investigating complex cognitive processes. The authors' current SDT ideal observer analysis of the model demonstrates that related priming does not directly alter sensitivity and that unrelated priming increases only false-alarm rate, reducing sensitivity. This analysis provides new perspectives on SDT concepts of complex decision processing.

"Nonparametric" A' and other modern misconceptions about signal detection theory.

Many modern descriptions of signal detection theory (SDT) are, at best, distorted caricatures of the Gaussian equal-variance model of SDT (G-SDT). The distortions have sometimes led to important, but unwarranted, conclusions about the nature of cognitive processes. Some researchers reject using d' and beta because of concerns about the validity of explicit underlying assumptions (that are shared with most inferential statistics), instead using either the supposedly "nonparametric" measures of A' and B" or measures known to confound ability and bias. The origins, development, and underlying assumptions of SDT are summarized, then contrasted with modern distortions and misconceptions. The nature and interpretation of common descriptive statistics for sensitivity and bias are described along with important pragmatic considerations about use. A deeper understanding of SDT provides researchers with tools that better evaluate both their own findings and the validity of conclusions drawn by others who have utilized SDT measures and analyses.