A cautionary tale on the effects of different covariance structures in linear mixed effects modeling of fMRI data.
Hum Brain Mapp
; 45(7): e26699, 2024 May.
Article
in En
| MEDLINE
| ID: mdl-38726907
ABSTRACT
With the steadily increasing abundance of longitudinal neuroimaging studies with large sample sizes and multiple repeated measures, questions arise regarding the appropriate modeling of variance and covariance. The current study examined the influence of standard classes of variance-covariance structures in linear mixed effects (LME) modeling of fMRI data from patients with pediatric mild traumatic brain injury (pmTBI; N = 181) and healthy controls (N = 162). During two visits, participants performed a cognitive control fMRI paradigm that compared congruent and incongruent stimuli. The hemodynamic response function was parsed into peak and late peak phases. Data were analyzed with a 4-way (GROUP×VISIT×CONGRUENCY×PHASE) LME using AFNI's 3dLME and compound symmetry (CS), autoregressive process of order 1 (AR1), and unstructured (UN) variance-covariance matrices. Voxel-wise results dramatically varied both within the cognitive control network (UN>CS for CONGRUENCY effect) and broader brain regions (CS>UN for GROUPVISIT) depending on the variance-covariance matrix that was selected. Additional testing indicated that both model fit and estimated standard error were superior for the UN matrix, likely as a result of the modeling of individual terms. In summary, current findings suggest that the interpretation of results from complex designs is highly dependent on the selection of the variance-covariance structure using LME modeling.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Magnetic Resonance Imaging
Limits:
Adolescent
/
Child
/
Female
/
Humans
/
Male
Language:
En
Journal:
Hum Brain Mapp
Journal subject:
CEREBRO
Year:
2024
Document type:
Article
Affiliation country:
Country of publication: