Description Usage Arguments Details Value Author(s) References See Also Examples
Calculates the network-based statistic (NBS), which allows for
family-wise error (FWE) control over network data, introduced for brain MRI
data by Zalesky et al. Accepts a three-dimensional array of all subjects'
connectivity matrices and a data.table
of covariates, and creates a
null distribution of the largest connected component size by permuting
subjects across groups. The covariates data.table
must have (at least)
a Group column.
1 2 3 4 |
A |
Three-dimensional array of all subjects' connectivity matrices |
covars |
A |
con.mat |
Numeric matrix specifying the contrast(s) of interest; if only one contrast is desired, you can supply a vector |
con.type |
Character string; either |
X |
Numeric matrix, if you wish to supply your own design matrix
(default: |
con.name |
Character vector of the contrast name(s); if |
p.init |
Numeric; the initial p-value threshold (default: |
N |
Integer; number of permutations to create (default: 5e3) |
perms |
Matrix of permutations, if you would like to provide your own
(default: |
symm.by |
Character string; how to create symmetric off-diagonal
elements (default: |
alternative |
Character string, whether to do a two- or one-sided test
(default: |
long |
Logical indicating whether or not to return all permutation
results (default: |
... |
Other arguments passed to |
The graph that is returned by this function will have a t.stat
edge
attribute which is the t-statistic for that particular connection, along with
a p
edge attribute, which is the p-value for that connection.
Additionally, each vertex will have a p.nbs
attribute representing
1 - the p-value associated with that vertex's component.
An object of class NBS
with some input arguments in addition
to:
X |
The design matrix |
removed |
Character vector of subject ID's removed due to incomplete data (if any) |
T.mat |
List of numeric matrices (symmetric) containing the statistics for each edge |
p.mat |
List of numeric matrices (symmetric) containing the P-values |
components |
List containing data tables of the observed and permuted connected component sizes and P-values |
Christopher G. Watson, [email protected]
Zalesky A., Fornito A., Bullmore E.T. (2010) Network-based statistic: identifying differences in brain networks. NeuroImage, 53(4):1197-1207.
brainGraph_GLM_design, brainGraph_GLM_fit_t
Other Group analysis functions: IndividualContributions
,
brainGraph_GLM
,
brainGraph_boot
,
brainGraph_mediate
,
brainGraph_permute
, mtpc
1 2 3 4 | ## Not run:
max.comp.nbs <- NBS(A.norm.sub[[1]], covars.dti, N=5e3)
## End(Not run)
|
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