Multiscale Adaptive Marginal Analysis of Longitudinal Neuroimaging Data with Time‐Varying Covariates

DOI10.1111/j.1541-0420.2012.01767.xzbMath1274.62876OpenAlexW2106392979WikidataQ34253546 ScholiaQ34253546MaRDI QIDQ4911931

Martha Skup, Heping Zhang, Hong-Tu Zhu

Publication date: 20 March 2013

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc3767131

zbMATH Keywords

smoothinggeneralized method of momentstime-varying covariatesmarginal modelingmultiscale adaptive regression modelvoxelwise method

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Point estimation (62F10) Neural biology (92C20) Biomedical imaging and signal processing (92C55)

Related Items (1)

Improved estimation in tensor regression with multiple change-points

Uses Software

• AWS
• spBayes

Cites Work

• Large Sample Properties of Generalized Method of Moments Estimators
• Longitudinal data analysis using generalized linear models
• Adaptive spatial smoothing of fMRI images
• Two-stage empirical likelihood for longitudinal neuroimaging data
• The statistical analysis of functional MRI data
• Longitudinal high-dimensional principal components analysis with application to diffusion tensor imaging of multiple sclerosis
• Multiscale Adaptive Regression Models for Neuroimaging Data
• A Caveat Concerning Independence Estimating Equations with Multivariate Binary Data
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