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This study introduces a new dataset on self-bias, the tendency to favor self-related information. It enables research into how self-bias operates across different cognitive, social, and economic decisions.

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Area of Science:

  • Cognitive Psychology
  • Social Psychology
  • Behavioral Economics

Background:

  • Self-bias, the systematic prioritization of self-related information, is documented across various domains.
  • Understanding the interrelationships between different self-bias manifestations is limited, hindering theoretical integration.

Purpose of the Study:

  • To present a comprehensive dataset on self-bias across cognitive, social, and economic decision-making.
  • To facilitate research on the underlying mechanisms and individual differences in self-bias.

Main Methods:

  • Collected trial-by-trial data from 134 participants across 10 established self-bias paradigms.
  • Included measures of individual differences such as personality traits, self-esteem, and self-construals.

Main Results:

  • The dataset captures diverse self-bias phenomena, including self-reference effect, mere ownership, and endowment effect.
  • Individual difference variables were collected to explore their moderating role in self-bias.

Conclusions:

  • This dataset serves as a foundation for investigating self-bias as a unitary construct or domain-specific phenomena.
  • It advances understanding of how self-relevance influences cognition and behavior.