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The Revelation Effect for Autobiographical Memory: A Mixture-Model Analysis

Author

Listed:
  • Bernstein, Daniel M.

    (Kwantlen Polytechnic University and University of Washington)

  • Rudd, Michael E.

    (University of Washington)

  • Erdfelder, Edgar

    (Universität Mannheim, Sonderforschungsbereich 504)

  • Godfrey, Ryan

    (University of California, Riverside)

  • Loftus, Elizabeth F.

    (University of California, Irvine)

Abstract

Participants provided information about their childhood by rating the confidence that they had experienced various events (e.g., 'broke a window playing ball'). On some trials, participants unscrambled a key word from the event-phrase (e.g., wdinwo – window) or an unrelated word (e.g., gnutge – nugget) before seeing the event and giving their confidence rating. Unscrambling led participants to increase their confidence that the event occurred in their childhood, but only when the confidence rating immediately followed the act of unscrambling. This increase in confidence mirrors the “revelation effect” observed in word recognition experiments. We analyze our data using a new signal detection mixture distribution model which does not require that the researcher knows the veracity of memory judgments a priori. Our analysis reveals that unscrambling a key word or an unrelated word affects response bias and discriminability in autobiographical memory tests in ways that are very similar to those that have been previously found for word recognition tasks.

Suggested Citation

  • Bernstein, Daniel M. & Rudd, Michael E. & Erdfelder, Edgar & Godfrey, Ryan & Loftus, Elizabeth F., 2008. "The Revelation Effect for Autobiographical Memory: A Mixture-Model Analysis," Sonderforschungsbereich 504 Publications 08-25, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
  • Handle: RePEc:xrs:sfbmaa:08-25
    Note: Financial support from the Deutsche Forschungsgemeinschaft, SFB 504, at the University of Mannheim, is gratefully acknowledged.
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