The general linear model (GLM) is the statistical method of choice used in brain morphometric analyses because of its ability to incorporate a multitude of effects. This chapter starts by presenting the theory, focusing on modeling, and then goes on discussing multiple comparisons issues specific to voxel-based approaches. The end of the chapter discusses practicalities: variable selection and covariates of no interest. Researchers have often a multitude of demographic and behavioral measures they wish to use, and methods to select such variables are presented. We end with a note of caution as the GLM can only reveal covariations between the brain and behavior, and prediction and causation mandate specific designs and analyses.
CITATION STYLE
Pernet, C. R. (2018). The general linear model: Theory and practicalities in brain morphometric analyses. In Neuromethods (Vol. 136, pp. 75–85). Humana Press Inc. https://doi.org/10.1007/978-1-4939-7647-8_5
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