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Should metacognition be measured by logistic regression?

Manuel Rausch1, Michael Zehetleitner1

  • 1Katholische Universität Eichstätt-Ingolstadt, Eichstätt, Germany; Ludwig-Maximilians-Universität München, Munich, Germany.

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Summary

Logistic regression slopes may not reliably measure metacognitive sensitivity. Their accuracy depends on specific metacognition models and requires controlling task and rating criteria, demanding extensive data.

Keywords:
Cognitive modelingGeneralized linear regressionLogistic regressionMetacognitionMetacognitive sensitivitySignal detection theoryType 2 signal detection theory

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Area of Science:

  • Cognitive Science
  • Neuroscience
  • Psychology
  • Decision Making

Background:

  • Metacognitive sensitivity quantifies how well subjective confidence reports distinguish correct from incorrect responses.
  • Logistic regression slopes are frequently used to estimate metacognitive sensitivity in behavioral studies.
  • The validity of logistic regression slopes across different metacognitive models remains an open question.

Purpose of the Study:

  • To analytically investigate whether logistic regression slopes are suitable for quantifying metacognitive sensitivity.
  • To determine the conditions under which logistic regression slopes are independent of rating and task criteria.
  • To compare the performance of logistic regression in distinguishing between different metacognitive models.

Main Methods:

  • Analytical derivation of logistic regression slopes under different metacognitive models.
  • Simulation studies to assess the accuracy of distinguishing between hierarchical and independent metacognition models.
  • Reanalysis of existing empirical data using the derived analytical frameworks.

Main Results:

  • Logistic regression slopes are independent of rating criteria only under a specific, restrictive model of metacognition.
  • In a hierarchical metacognition model, logistic regression slopes are dependent on rating criteria.
  • Across all models, logistic regression slopes are influenced by the primary task criterion, necessitating its control.

Conclusions:

  • Researchers must carefully consider the underlying metacognitive model when interpreting logistic regression slopes.
  • Accurate model discrimination requires a massive number of trials, highlighting practical limitations.
  • Controlling both primary task and rating criteria is essential for robust estimation of metacognitive sensitivity using logistic regression.