📚 Research Digest

Wednesday, May 06, 2026

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Identifying individual difference correlations when the data are noisy: A case study of proactive and reactive control Empirical 👍 👎
Jeffrey N. Rouder, Shanglin Yang, Todd Braver • PsyArXiv
Finding: Using hierarchical modeling to account for measurement error, researchers found that proactive and reactive cognitive control are only weakly correlated, supporting the Dual Mechanisms of Control framework's prediction of semi-independent control systems.

Why it matters: This demonstrates methodological approaches for measuring individual differences in cognitive control mechanisms that influence decision-making and goal-directed behavior.

Method: Applied hierarchical modeling to a large Stroop task dataset to simultaneously estimate measurement error and individual covariation, providing disattenuated correlation estimates with proper uncertainty quantification.

Jargon: Proactive control = anticipatory cognitive control engaged before stimulus onset; Reactive control = cognitive control triggered by stimulus/response features; DMC = Dual Mechanisms of Control framework.
⚠️ No control group mentioned | Single study (not replicated)
📖 Plain-language summary
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