bootThreshold: Threshold network based on bootstrapped intervals

Description

This function takes the output of bootnet and returns a network as if it had been estimated using estimateNetwork, but with edges removed (set to zero) based on some significance level.

Usage

bootThreshold(bootobject, alpha = 0.05, verbose = TRUE, thresholdIntercepts = FALSE)

Value

A bootnetResult object with the following elements:

graph: The weights matrix of the network
intercepts: The intercepts
results: The results of the estimation procedure
labels: A vector with node labels
nNodes: Number of nodes in the network
nPerson: Number of persons in the network
input: Input used, including the result of the default set used

Arguments

bootobject: Nonparametric bootstrap results from bootnet
alpha: Significance level
verbose: Logical, should progress be reported to the console?
thresholdIntercepts: Logical, should intercepts also be thresholded?

Author

Sacha Epskamp <mail@sachaepskamp.com>

Examples

Run this code

if (FALSE) {
# BFI Extraversion data from psychTools package:
library("psychTools")
data(bfi)
bfiSub <- bfi[,1:25]

# Estimate unregularized network:
Network <- estimateNetwork(bfiSub, default = "pcor", corMethod = "cor")

# Bootstrap 1000 values, using 8 cores:
boots <- bootnet(Network, nBoots = 1000, nCores = 8)

# Threshold network:
Network_thresholded <- bootThreshold(boots)

# Plot:
plot(Network_thresholded)
}