Testing separability and independence of perceptual dimensions with general recognition theory: A tutorial and new R package (grtools)

TL;DR

This paper introduces grtools, an R package that simplifies testing perceptual independence using General Recognition Theory, making advanced analysis accessible for experimental psychologists and neuroscientists.

Contribution

It provides a user-friendly R package and tutorial for applying GRT analyses, filling a gap in accessible software for perceptual independence testing.

Findings

Provides a comprehensive R package for GRT analysis

Includes practical tutorial and best practice advice

Facilitates wider adoption of GRT in perceptual research

Abstract

Determining whether perceptual properties are processed independently is an important goal in perceptual science, and tools to test independence should be widely available to experimental researchers. The best analytical tools to test for perceptual independence are provided by General Recognition Theory (GRT), a multidimensional extension of signal detection theory. Unfortunately, there is currently a lack of software implementing GRT analyses that is ready-to-use by experimental psychologists and neuroscientists with little training in computational modeling. This paper presents grtools, an R package developed with the explicit aim of providing experimentalists with the ability to perform full GRT analyses using only a couple of command lines. We describe the software and provide a practical tutorial on how to perform each of the analyses available in grtools. We also provide advice to researchers on best practices for experimental design and interpretation of results.