corStability {bootnet} | R Documentation |
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 |
cor |
The correlation level tot est at. |
statistics |
The statistic(s) to test for. Can also be |
verbose |
Logical, should information on the progress be printed to the console? |
Author(s)
Sacha Epskamp <mail@sachaepskamp.com>
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
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)