corStability: Correlation stability coefficient

Description Usage Arguments Author(s) References See Also Examples

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

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corStability(x, cor = 0.7, statistics = c("strength", "closeness", "betweenness"), 
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.

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

bootnet

Examples

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## Not run: 
# BFI Extraversion data from psych package:
library("psych")
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)


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