A multiverse assessment of the reliability of the self-matching task as a measurement of the self-prioritization effect

The self-matching task (SMT) is widely used to investigate the cognitive mechanisms underlying the self-prioritization effect (SPE), wherein performance is enhanced for self-associated stimuli compared to other-associated ones. Although the SMT robustly elicits the SPE, there is a lack of data quantifying the reliability of this paradigm. This is problematic, given the prevalence of the reliability paradox in cognitive tasks: many well-established cognitive tasks demonstrate relatively low reliability when used to evaluate individual differences, despite exhibiting replicable effects at the group level. To fill this gap, this preregistered study investigated the reliability of SPE derived from the SMT using a multiverse approach, combining all possible indicators and baselines reported in the literature. We first examined the robustness of 24 SPE measures across 42 datasets (N = 2250) using a meta-analytical approach. We then calculated the split-half reliability (r) and intraclass correlation coefficient (ICC2) for each SPE measure. Our findings revealed a robust group-level SPE across datasets. However, when evaluating individual differences, SPE indices derived from reaction time (RT) and efficiency exhibited relatively higher, compared to other SPE indices, but still unsatisfied split-half reliability (approximately 0.5). The reliability across multiple time points, as assessed by ICC2, RT, and efficiency, demonstrated moderate levels of test-retest reliability (close to 0.5). These findings revealed the presence of a reliability paradox in the context of SMT-based SPE assessment. We discussed the implications of how to enhance individual-level reliability using this paradigm for future study design.