get_connectivity: Get Brain Connectivity Measures
In TysonStanley/connectivity: Tools to Assess Brain Connectivity
View source: R/get_connections.R
Description
Provides measures of connectivity between brain regions from a nested tibble returned from 'import_nirs()'. It
fits the data to a multilevel model with a specified number of lags. It returns a tibble with effect size measures
to and from each region.
Usage
1
Arguments
data
object from a nested tibble returned from 'import_nirs()'
group
the group variable to have interact with the regions, to answer the question of if the connectivity is different across groups
covariates
variables to include in the model in addition to the regions of interest and the random effects
...
arguments passed to 'lme4::lmer()'
TysonStanley/connectivity documentation built on March 15, 2020, 1:44 a.m.
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View source: R/get_connections.R
Description
Provides measures of connectivity between brain regions from a nested tibble returned from 'import_nirs()'. It fits the data to a multilevel model with a specified number of lags. It returns a tibble with effect size measures to and from each region.
Usage
1 |
Arguments
data |
object from a nested tibble returned from 'import_nirs()' |
group |
the group variable to have interact with the regions, to answer the question of if the connectivity is different across groups |
covariates |
variables to include in the model in addition to the regions of interest and the random effects |
... |
arguments passed to 'lme4::lmer()' |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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