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A Generalized Estimating Equations Approach for Resting-State Functional MRI Group Analysis
- Source :
- EMBC
- Publication Year :
- 2011
-
Abstract
- An Alzheimer's fMRI study has motivated us to evaluate inter-regional correlations between groups. The overall objective is to assess inter-regional correlations at a resting-state with no stimulus or task. We propose using a generalized estimating equation (GEE) transition model and a GEE marginal model to model the within-subject correlation for each region. Residuals calculated from the GEE models are used to correlate brain regions and assess between group differences. The standard pooling approach of group averages of the Fisher-z transformation assuming temporal independence is a typical approach used to compare group correlations. The GEE approaches and standard Fisher-z pooling approach are demonstrated with an Alzheimer's disease (AD) connectivity study in a population of AD subjects and healthy control subjects. We also compare these methods using simulation studies and show that the transition model may have better statistical properties.
- Subjects :
- education.field_of_study
Resting state fMRI
Rest
Population
Pooling
Brain
Reproducibility of Results
Marginal model
Magnetic Resonance Imaging
Sensitivity and Specificity
Gee
Article
Correlation
Group analysis
Alzheimer Disease
Statistics
Image Interpretation, Computer-Assisted
Econometrics
Humans
education
Psychology
Generalized estimating equation
Algorithms
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- EMBC
- Accession number :
- edsair.doi.dedup.....455fa887c1dda7e17fee527fefc156fd