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A spurious correlation between difference scores in evidence-accumulation model parameters.

James A Grange1, Stefanie Schuch2

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Summary
This summary is machine-generated.

Evidence-accumulation models are key for understanding cognitive processes. Researchers must be cautious, as model parameter difference scores can show spurious correlations, particularly between boundary and non-decision time differences.

Keywords:
CorrelationsDiffusion modellingIndividual differencesRT difference scores

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Area of Science:

  • Cognitive psychology
  • Computational neuroscience
  • Psychometrics

Background:

  • Evidence-accumulation models are widely used to analyze reaction times and error rates.
  • These models quantify cognitive processes using parameters like drift rate, boundary, and non-decision time.
  • Researchers often examine experimental effects by calculating difference scores between model parameters across conditions.

Purpose of the Study:

  • To investigate spurious correlations between evidence-accumulation model parameter difference scores.
  • To determine the conditions under which these spurious correlations arise in simulations and empirical data.
  • To caution researchers against over-interpreting correlational findings based on model parameter differences.

Main Methods:

  • Computer simulations of evidence-accumulation models under various manipulation conditions.
  • Analysis of empirical behavioral data using evidence-accumulation models.
  • Calculation and correlation of difference scores for model parameters (drift rate, boundary, non-decision time).

Main Results:

  • A pronounced spurious negative correlation (r = -0.70 or larger) was observed between boundary difference and non-decision difference scores.
  • This spurious correlation appeared in simulations when no true parameter differences existed or only drift rate was manipulated.
  • The spurious correlation disappeared when true differences in boundary, non-decision time, or all parameters were simulated.

Conclusions:

  • Difference scores derived from evidence-accumulation model parameters can exhibit spurious correlations.
  • These correlations may arise artifactually, independent of true inter-individual differences at the population level.
  • Researchers should exercise caution when employing correlational analyses with evidence-accumulation model parameter difference scores.