NBS — NBS_lme • FCtools

Network-based statistics analysis

Usage

NBS_lme(
  model,
  contrast,
  random,
  FC_data,
  nperm = 100,
  nthread = 1,
  p = 0.001,
  perm_type = "row"
)

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
random: A N x 1 numeric vector or object containing the values of the random variable (optional). Its length should be equal to the number of subjects in model (it should NOT be inside the model data.frame).
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
perm_type: A string object specifying whether to permute the rows ("row"), between subjects ("between"), within subjects ("within") or between and within subjects ("within_between") for random subject effects. Default is "row".

Returns 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

This function implements the NBS analysis described in Zalesky et al. (2010)

if (FALSE) { # \dontrun{
model1=NBS_lme(model,contrast, random, FC_data, nperm=1000, nthread=8, p=0.001)
} # }