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Exploratory factor analysis with structured residuals for brain network data
2020
Network Neuroscience
Dimension reduction is widely used and often necessary to make network analyses and their interpretation tractable by reducing high dimensional data to a small number of underlying variables. Techniques such as Exploratory Factor Analysis (EFA) are used by neuroscientists to reduce measurements from a large number of brain regions to a tractable number of factors. However, dimension reduction often ignores relevant a priori knowledge about the structure of the data. For example, it is well
doi:10.1162/netn_a_00162
pmid:33688604
pmcid:PMC7935039
fatcat:hrqi527uirbltexo6b4x2t3xme