corStability: Correlation stability coefficient

In bootnet: Bootstrap Methods for Various Network Estimation Routines

Correlation stability coefficient

Description

This coefficient denotes the estimated maximum number of cases that can be dropped from the data to retain, with 95% probability, a correlation of at least 0.7 (default) between statistics based on the original network and statistics computed with less cases. This coefficient should not be below 0.25 and is preferably above 0.5. See also Epskamp, Borsboom and Fried (2016) for more details.

Usage

corStability(x, cor = 0.7, statistics = "all", verbose = TRUE)

Arguments

x	Output of bootnet. Must be case-drop bootstrap.
cor	The correlation level tot est at.
statistics	The statistic(s) to test for. Can also be "all".
verbose	Logical, should information on the progress be printed to the console?

Author(s)

Sacha Epskamp <[e-mail]>

References

Epskamp, S., Borsboom, D., & Fried, E. I. (2016). Estimating psychological networks and their accuracy: a tutorial paper. arXiv preprint, arXiv:1604.08462.

See Also

bootnet

Examples

## Not run: 
# BFI Extraversion data from psychTools package:
library("psychTools")
data(bfi)
bfiSub <- bfi[,1:25]

# Estimate network:
Network <- estimateNetwork(bfiSub, default = "EBICglasso")

# Bootstrap 1000 values, using 8 cores:
# Bootstrap 1000 values, using 8 cores:
Results2 <- bootnet(Network, nBoots = 1000, nCores = 8, 
              type = "case")

# Compute CS-coefficients:
corStability(Results2)

## End(Not run)

bootnet documentation built on May 29, 2024, 8:38 a.m.