Linear mixed-effects modeling approach to FMRI group analysis

• Published in: NeuroImage (Orlando, Fla.) Vol. 73; pp. 176 - 190
• Main Authors: Chen, Gang, Saad, Ziad S., Britton, Jennifer C., Pine, Daniel S., Cox, Robert W.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Inc 01.06.2013; Elsevier; Elsevier Limited
• Subjects: AFNI; Age; Algorithms; AN(C)OVA; Analysis of Variance; Biological and medical sciences; Computer Simulation; Data Interpretation, Statistical; FMRI group analysis; Fundamental and applied biological sciences. Psychology; GLM; Hemodynamics - physiology; Humans; ICC; Image Processing, Computer-Assisted; Linear Models; LME; Longitudinal Studies; Magnetic Resonance Imaging - methods; Magnetic Resonance Imaging - statistics & numerical data; Models, Neurological; Normal Distribution; Regression analysis; Scanners; Software; Symmetry; Twin Studies as Topic; Variables; Vertebrates: nervous system and sense organs; AN(C)OVA; R; LME; FMRI group analysis; ICC; GLM; AFNI; Nuclear magnetic resonance imaging; Functional imaging

Conventional group analysis is usually performed with Student-type t-test, regression, or standard AN(C)OVA in which the variance–covariance matrix is presumed to have a simple structure. Some correction approaches are adopted when assumptions about the covariance structure is violated. However, as...