Detecting chance: a solution to the null sensitivity problem in subliminal priming.

In many paradigms, the persuasiveness of subliminal priming relies on establishing that stimuli are undetectable. The standard significance test approach is ill-suited as null results may reflect either truly undetectable stimuli or a lack of power to resolve weakly detectable stimuli. We present a novel statistical model as an alternative. The model provides for estimates of the probability that each individual is truly at chance. Researchers may select individuals for whom there are sufficiently high probabilities of true undetectability. The model is hierarchical, and estimation is done within the Bayesian framework.