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

Implements network analysis and graph theory measures used in neuroscience, cognitive science, and psychology. Methods include various filtering methods and approaches such as threshold, dependency (Kenett, Tumminello, Madi, Gur-Gershogoren, Mantegna, & Ben-Jacob, 2010 <doi:10.1371/journal.pone.0015032>), Information Filtering Networks (Barfuss, Massara, Di Matteo, & Aste, 2016 <doi:10.1103/PhysRevE.94.062306>), and Efficiency-Cost Optimization (Fallani, Latora, & Chavez, 2017 <doi:10.1371/journal.pcbi.1005305>). Brain methods include the recently developed Connectome Predictive Modeling (see references in package). Also implements several network measures including local network characteristics (e.g., centrality), community-level network characteristics (e.g., community centrality), global network characteristics (e.g., clustering coefficient), and various other measures associated with the reliability and reproducibility of network analysis.

Version: 1.2.0
Depends: R (≥ 3.3.0)
Imports: Matrix, psych, corrplot, fdrtool, R.matlab, MASS, pwr, igraph, qgraph, ppcor, parallel, foreach, doParallel
Published: 2018-07-25
Author: Alexander Christensen
Maintainer: Alexander Christensen <alexpaulchristensen at>
License: GPL (≥ 3.0)
NeedsCompilation: no
Citation: NetworkToolbox citation info
Materials: NEWS
CRAN checks: NetworkToolbox results


Reference manual: NetworkToolbox.pdf
Package source: NetworkToolbox_1.2.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: NetworkToolbox_1.2.0.tgz, r-oldrel: NetworkToolbox_1.2.0.tgz
Old sources: NetworkToolbox archive

Reverse dependencies:

Reverse imports: bootnet


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