Associative Learning
Collisions in Multiple Dimensions: Introduction
Collisions in Multiple Dimensions: Problem Solving
Association Areas of the Cortex
Correlation of Experimental Data
Stereotypes, Prejudice, and Discrimination
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Updated: Mar 24, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
Published on: March 1, 2022
Ben Murrell1, Daniel Murrell2, Hugh Murrell3
1Department of Medicine, University of California San Diego, San Diego, United States of America.
We developed a new method to estimate explained variance (R2) for unknown relationships, outperforming existing measures like Maximal Information Coefficient (MIC). This approach works in multiple dimensions and controls for covariates, offering a robust way to measure variable association.
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