NetworkToolbox: threshold – R documentation

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threshold

Threshold Network Estimation Methods

Description

Filters the network based on an r-value, alpha, adaptive alpha, bonferroni, false-discovery rate (FDR), or proportional density (fixed number of edges) value

Usage

threshold(
  data,
  a,
  thresh = c("alpha", "adaptive", "bonferroni", "FDR", "proportional"),
  normal = FALSE,
  na.data = c("pairwise", "listwise", "fiml", "none"),
  ...
)

Arguments

`data`	Can be a dataset or a correlation matrix
`a`	When `thresh = "alpha"`, `"adaptive"`, and `"bonferroni"` an α threshold is applied (defaults to `.05`). For `"adaptive"`, beta (Type II error) is set to α5* for a medium effect size (r = .3). When `thresh = "FDR"`, a q-value threshold is applied (defaults to `.10`). When `thresh = "proportional"`, a density threshold is applied (defaults to `.15`)
`thresh`	Sets threshold. Defaults to `"alpha"`. Set to any value 0> r >1 to retain values greater than set value, `"adaptive"` for an `adapt.a` based on sample size (Perez & Pericchi, 2014), `"bonferroni"` for the bonferroni correction on alpha, `"FDR"` for local false discovery rate, and `"proportional"` for a fixed density of edges (keeps strongest correlations within density)
`normal`	Should data be transformed to a normal distribution? Defaults to FALSE. Data is not transformed to be normal. Set to TRUE if data should be transformed to be normal (computes correlations using the cor_auto function)
`na.data`	How should missing data be handled? For `"listwise"` deletion the `na.omit` function is applied. Set to `"fiml"` for Full Information Maximum Likelihood (`corFiml`). Full Information Maximum Likelihood is recommended but time consuming
`...`	Additional arguments for `fdrtool` and `adapt.a`

Value

Returns a list containing:

`A`	The filtered adjacency matrix
`r.cv`	The critical correlation value used to filter the network

Author(s)

Alexander Christensen <alexpaulchristensen@gmail.com>

References

Strimmer, K. (2008). fdrtool: A versatile R package for estimating local and tail area-based false discovery rates. Bioinformatics, 24, 1461-1462.

Examples

threshnet<-threshold(neoOpen)

alphanet<-threshold(neoOpen, thresh = "alpha", a = .05)

bonnet<-threshold(neoOpen, thresh = "bonferroni", a = .05)

FDRnet<-threshold(neoOpen, thresh = "FDR", a = .10)

propnet<-threshold(neoOpen, thresh = "proportional", a = .15)

NetworkToolbox

Methods and Measures for Brain, Cognitive, and Psychometric Network Analysis

v1.4.1

GPL (>= 3.0)

Authors

Alexander Christensen [aut, cre] (<https://orcid.org/0000-0002-9798-7037>), Guido Previde Massara [ctb] (<https://orcid.org/0000-0003-0502-2789>)

Initial release

2020-12-07