[Face-research-list] grtools: Analyze perceptual independence using general recognition theory (a.k.a. multidimensional signal detection theory) in R

Dear colleagues, We have developed a new R package, called grtools, that can be used to analyze psychophysical data to determine the independence and separability of perceptual dimensions. The analyses use general recognition theory (GRT; a.k.a multidimensional signal detection theory) to test for perceptual independence and separability while controlling for the influence of decisional processes. We designed the package to be easy to use for non-experts. Thus, full analyses can be performed through only a couple of commands. grtools provides functions for the following analyses: 1. Model-based analyses of separability and independence using the GRT-wIND (GRT with INdividual Differences) model of identification data. 2. Model-based analyses of separability and independence using traditional GRT models of identification data. 3. Summary statistics analyses (i.e., Kadlec's MSDA) of identification data. 4. Summary statistics analyses of data from the Garner filtering task. For more information and instructions on how to install the package, please visit the following page: https://github.com/fsotoc/grtools Best, Fabian A. Soto F. Gregory Ashby -- Fabian A. Soto Postdoctoral Researcher Department of Psychological and Brain Sciences University of California Santa Barbara Santa Barbara, CA 93106 E-mail: fabian.soto(a)psych.ucsb.edu Website: http://people.psych.ucsb.edu/soto/fabian/