brainGraph (version 2.7.3)

NBS: Network-based statistic for brain MRI data

Description

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.

Usage

NBS(A, covars, con.mat, con.type = c("t", "f"), X = NULL,
  con.name = NULL, p.init = 0.001, N = 1000, perms = NULL,
  symm.by = c("max", "min", "avg"), alternative = c("two.sided",
  "less", "greater"), long = FALSE, ...)
# S3 method for NBS
summary(object, contrast = NULL, digits = max(3L,
  getOption("digits") - 2L), ...)

Arguments

A

Three-dimensional array of all subjects' connectivity matrices

covars

A data.table of covariates

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 't' or 'f' (for t or F-statistics). Default: 't'

X

Numeric matrix, if you wish to supply your own design matrix (default: NULL)

con.name

Character vector of the contrast name(s); if con.mat has row names, those will be used for reporting results (default: NULL)

p.init

Numeric; the initial p-value threshold (default: 0.001)

N

Integer; number of permutations to create (default: 5e3)

perms

Matrix of permutations, if you would like to provide your own (default: NULL)

symm.by

Character string; how to create symmetric off-diagonal elements (default: max)

alternative

Character string, whether to do a two- or one-sided test (default: 'two.sided')

long

Logical indicating whether or not to return all permutation results (default: FALSE)

...

Other arguments passed to brainGraph_GLM_design

object

A NBS object

contrast

Integer specifying the contrast to plot/summarize; defaults to showing results for all contrasts

digits

Integer specifying the number of digits to display for p-values

Value

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

3-d array of (symmetric) numeric matrices containing the statistics for each edge

p.mat

3-d array of (symmetric) numeric matrices containing the P-values

components

List containing data tables of the observed and permuted connected component sizes and P-values

Details

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.

References

Zalesky A., Fornito A., Bullmore E.T. (2010) Network-based statistic: identifying differences in brain networks. NeuroImage, 53(4):1197-1207.

See Also

brainGraph_GLM_design, brainGraph_GLM_fit_t

Other Group analysis functions: Bootstrapping, GLM, IndividualContributions, MediationAnalysis, brainGraph_permute, mtpc

Examples

# NOT RUN {
max.comp.nbs <- NBS(A.norm.sub[[1]], covars.dti, N=5e3)
# }