network_lm — network_lm • FCtools

mass univariate linear regression at the network level

Usage

network_lm(
  model,
  contrast,
  FC_data,
  threshold.method = "fdr",
  perm = T,
  nperm = 1000
)

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
threshold.method: method for correcting for multiple tests. set to fdr by default
perm: If set to TRUE, p values will be calculated using a permutation approach by shuffling subjects' labels, before correcting for FDR. Set to TRUE by default
nperm: number of permutations to use if perm=T.

Value

Returns a data.frame object with coef and corrected p values

Details

This function first summarizes the FC edges into their respective networks and then carry out mass univariate linear regression analyses on each of the network to network connection

Examples

if (FALSE) { # \dontrun{
model1=network_lm(model,contrast, FC_data)
} # }