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Inferring latent hemispheric differences from observed laterality measures
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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.
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