Raising awareness about measurement error in research on unconscious mental processes

Experimental psychologists often neglect the poor psychometric properties of the dependent measures collected in their studies. In particular, a low reliability of measures can have dramatic consequences for the interpretation of key findings in some of the most popular experimental paradigms, especially when strong inferences are drawn from the absence of statistically significant correlations. In research on unconscious cognition, for instance, it is commonly argued that the lack of a correlation between task performance and measures of awareness or explicit recollection of the target stimuli provides strong support for the conclusion that the cognitive processes underlying performance must be unconscious. Using contextual cuing of visual search as a case study, we show that given the low reliability of the dependent measures collected in these studies, it is usually impossible to draw any firm conclusion about the unconscious character of this effect from correlational analyses. Furthermore, both a psychometric meta-analysis of the available evidence and a cognitive-modeling approach suggest that, in fact, we should expect to see very low correlations between performance and awareness at the empirical level, even if both constructs are perfectly related at the latent level. Convincing evidence for the unconscious character of contextual cuing and other effects will most likely demand richer and larger datasets, coupled with more powerful analytic approaches.

The problem of the null in the verification of unconscious cognition

Newell & Shanks (N&S) argue that when awareness measures are more reliable and valid, greater evidence of awareness of supposedly unconscious influences is revealed. A related issue is that unconsciousness is typically the null hypothesis that evidence of awareness will not emerge. As it is difficult to conclude the null, it is also difficult to conclude a lack of conscious awareness.