In cognitive science, researchers typically focus on the average effect within a population. However, an alternative approach is to analyze each participant individually to determine how likely they are to show the desired effect. This method, known as within-participant statistics, offers both conceptual and practical advantages. It allows for a deeper understanding of the impact at an individual level, potentially uncovering new insights that may be masked in population averages. By examining the prevalence or participant replication probability, researchers can assess the proportion of the population that would exhibit the effect. This approach opens doors to personalized analysis and tailoring interventions based on individual needs. Further exploration of within-participant statistics could lead to more nuanced interpretations of cognitive science research. To learn more about this innovative approach, check out the full article!
