NBS

Network-based statistics analysis

Usage

NBS(model, contrast, FC_data, nperm = 100, nthread = 1, p = 0.001)

Arguments

model

A data.frame or matrix containing all the predictors in the model

contrast

The predictor of interest. The edge- and network-wise statistics will only be estimated for this predictor

FC_data

An N x E matrix containing the vectorized edges; where N = number of subjects, E=number of edges

nperm

The number of permutations to generate the null distribution of network strengths. Set to 100 by default

nthread

The number of CPU threads to use. Set to 1 by default

p

the edge-wise threshold. Set to 0.001 by default

Value

A list object containing

• results Edge- and network-wise results in a data.frame object

• t.orig Edge-wise t-stats

• tcrit The critical t-value

• max.netstr A vector containing the null distribution of the permuted network strengths

Details

This function implements the NBS analysis described in Zalesky et al. (2010) doi:10.1016/j.neuroimage.2010.06.041

Examples

demomat=get('demomat')[,1:7021] 
contrast=c(1,1,2,2)
random=c('sub1','sub2','sub3','sub4')
model1=NBS(model=contrast, 
           contrast=contrast, 
           FC_data=demomat, 
           nperm=2, 
           nthread=2, 
           p=0.001)
#> 
  |                                                                            
  |                                                                      |   0%
#> Estimating permuted network strengths...
#> 
  |                                                                            
  |===================================                                   |  50%
  |                                                                            
  |======================================================================| 100%
#> Completed in :0.1 minutes