qgraph: FDRnetwork – R documentation

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FDRnetwork

Model selection using local False Discovery Rate

Description

This function is a wrapper arounf fdrtool to easilly compute a correlation or partial correlation network in which all nonsignificant edges are set to zero.

Usage

FDRnetwork(net, cutoff = 0.1, method = c('lfdr', 'pval', 'qval'))

Arguments

`net`	A correlation or partial correlation matrix
`cutoff`	The cutoff value to use. The edges of which the value of the first element of `method` are higher than the cutoff are removed. Thus, by default, edges with a local false discovery rate of higher than 0.1 are removed from the graph.
`method`	The method to use with the cutoff. Can be `'lfdr'` for the local false discobvery rate, `'pval'` for the p-value of `'qval'` for the q-value.

Details

method = 'lfdr' could result in a very sparse network, so also looking at other values is advisable.

Author(s)

Sacha Epskamp <mail@sachaepskamp.com>

References

Bernd Klaus and Korbinian Strimmer. (2014). fdrtool: Estimation of (Local) False Discovery Rates and Higher Criticism. R package version 1.2.12. http://CRAN.R-project.org/package=fdrtool

Examples

## Not run: 
### Using bfi dataset from psych ###
library("psych")
data(bfi)

### CORRELATIONS ###
# Compute correlations:
CorMat <- cor_auto(bfi[,1:25])

# Run local FDR:
CorMat_FDR <- FDRnetwork(CorMat)

# Number of edges remaining:
mean(CorMat_FDR[upper.tri(CorMat_FDR,diag=FALSE)]!=0)

# None, so might use different criterion:
CorMat_FDR <- FDRnetwork(CorMat, method = "pval")


# Compare:
L <- averageLayout(CorMat, CorMat_FDR)

layout(t(1:2))
qgraph(CorMat, layout = L, title = "Correlation network", 
       maximum = 1, cut = 0.1, minimum = 0, esize = 20)
qgraph(CorMat_FDR, layout = L, title = "Local FDR correlation network", 
       maximum = 1, cut = 0.1, minimum = 0, esize = 20)

# Centrality:
centralityPlot(list(cor=CorMat, fdr = CorMat_FDR))


### PARTIAL CORRELATIONS ###
# Partial correlation matrix:
library("parcor")
PCorMat <- cor2pcor(CorMat)

# Run local FDR:
PCorMat_FDR <- FDRnetwork(PCorMat, cutoff = 0.1, method = "pval")

# Number of edges remaining:
mean(PCorMat_FDR[upper.tri(PCorMat_FDR,diag=FALSE)]!=0)

# Compare:
L <- averageLayout(PCorMat, PCorMat_FDR)

layout(t(1:2))
qgraph(PCorMat, layout = L, title = "Partial correlation network", 
          maximum = 1, cut = 0.1, minimum = 0, esize = 20)
qgraph(PCorMat_FDR, layout = L, title = "Local FDR partial correlation network", 
          maximum = 1, cut = 0.1, minimum = 0, esize = 20)

# Centrality:
centralityPlot(list(cor=PCorMat, fdr = PCorMat_FDR))

## End(Not run)

qgraph

Graph Plotting Methods, Psychometric Data Visualization and Graphical Model Estimation

v1.6.9

GPL-2

Authors

Sacha Epskamp [aut, cre], Giulio Costantini [aut], Jonas Haslbeck [aut], Adela Isvoranu [aut], Angelique O. J. Cramer [ctb], Lourens J. Waldorp [ctb], Verena D. Schmittmann [ctb], Denny Borsboom [ctb]

Initial release