Improving mass-univariate analysis of neuroimaging data by modelling important unknown covariates: Application to Epigenome-Wide Association Studies.
Guillaume, Bryan
Improving mass-univariate analysis of neuroimaging data by modelling important unknown covariates: Application to Epigenome-Wide Association Studies. [electronic resource] - NeuroImage 06 2018 - 57-71 p. digital
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
1095-9572
10.1016/j.neuroimage.2018.01.073 doi
Computer Simulation
Data Interpretation, Statistical
Genome-Wide Association Study--methods
Humans
Linear Models
Longitudinal Studies
Models, Statistical
Neuroimaging--methods
Improving mass-univariate analysis of neuroimaging data by modelling important unknown covariates: Application to Epigenome-Wide Association Studies. [electronic resource] - NeuroImage 06 2018 - 57-71 p. digital
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
1095-9572
10.1016/j.neuroimage.2018.01.073 doi
Computer Simulation
Data Interpretation, Statistical
Genome-Wide Association Study--methods
Humans
Linear Models
Longitudinal Studies
Models, Statistical
Neuroimaging--methods