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Inferring latent hemispheric differences from observed laterality measures
Date created: 2020-02-28 01:07 PM | Last Updated: 2020-09-23 11:47 AM
Identifier: DOI 10.17605/OSF.IO/MKWCR
Category: Project
Description: Functional differences between the cerebral hemispheres are a fundamental characteristic of the human brain. Researchers interested in studying these differences often infer underlying hemispheric dominance for a certain function (e.g., language) from laterality indices calculated from observed performance or brain activation measures . However, any inference from observed measures to latent (unobserved) classes has to consider the antecedent probability of class membership in the population. The present project provides a Bayesian model for valid inferences as well as scripts designed to facilitate the application of the model in research.
An R package containing an implementation of the algorithm developed in the paper is available at: https://cran.r-project.org/web/packages/BayesianLaterality/index.html
A Shiny app for easy exploration of the concepts presented in the paper is available at https://osorensen.shinyapps.io/BayesianLateralityApp/.
The publication is now published in Laterality as open access: https://doi.org/10.1080/1…
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