Progressing, not regressing: A possible solution to the problem of regression to the mean in unconscious processing studies

Itay Yaron*, Yoav Zeevi, Uri Korisky, William Marshall, Liad Mudrik

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


How convincing is current evidence for unconscious processing? Recently, a major criticism suggested that some, if not much, of this evidence might be explained by a mere statistical phenomenon: regression to the mean (RttM). Excluding participants based on an awareness assessment is a common practice in studies of unconscious processing, and this post hoc data selection might lead to false effects that are driven by RttM for aware participants wrongfully classified as unaware. Here, we examined this criticism using both simulations and data from 12 studies probing unconscious processing (35 effects overall). In line with the original criticism, we confirmed that the reliability of awareness measures in the field is concerningly low. Yet, using simulations, we showed that reliability measures might be unsuitable for estimating error in awareness measures. Furthermore, we examined other solutions for assessing whether an effect is genuine or reflects RttM; all suffered from substantial limitations, such as a lack of specificity to unconscious processing, lack of power, or unjustified assumptions. Accordingly, we suggest a new nonparametric solution, which enjoys high specificity and relatively high power. Together, this work emphasizes the need to account for measurement error in awareness measures and evaluate its consequences for unconscious processing effects. It further suggests a way to meet the important challenge posed by RttM, in an attempt to establish a reliable and robust corpus of knowledge in studying unconscious processing.

Original languageEnglish
Pages (from-to)49-64
Number of pages16
JournalPsychonomic Bulletin and Review
Issue number1
StatePublished - Feb 2024


FundersFunder number
Consciousness program
Natural Sciences and Engineering Research Council of CanadaRGPIN-2019-05418


    • Consciousness
    • Power
    • Regression to the mean
    • Reliability
    • Unconscious processing


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