Statistical analysis of longitudinal neuroimage data with Linear Mixed Effects models

• Published in: NeuroImage (Orlando, Fla.) Vol. 66; pp. 249 - 260
• Main Authors: Bernal-Rusiel, Jorge L., Greve, Douglas N., Reuter, Martin, Fischl, Bruce, Sabuncu, Mert R.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Inc 01.02.2013; Elsevier; Elsevier Limited
• Subjects: Aged; Aged, 80 and over; Algorithms; Alzheimer Disease - pathology; Biological and medical sciences; Brain - pathology; Cognitive Dysfunction - pathology; Female; Fundamental and applied biological sciences. Psychology; Humans; Hypothesis testing; Image Processing, Computer-Assisted - methods; Linear Mixed Effects models; Linear Models; Longitudinal Studies; Magnetic Resonance Imaging; Male; Medical imaging; Middle Aged; Parameter estimation; Software; Standard deviation; Statistical analysis; Statistical methods; Studies; Variance analysis; Vertebrates: nervous system and sense organs; Linear Mixed Effects models; Longitudinal studies; Statistical analysis; Models

Longitudinal neuroimaging (LNI) studies are rapidly becoming more prevalent and growing in size. Today, no standardized computational tools exist for the analysis of LNI data and widely used methods are sub-optimal for the types of data encountered in real-life studies. Linear Mixed Effects (LME) mo...