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psychnets  

Tidy Clean-Room Psychological Network Modeling
View on CRAN: Click here


Download and install psychnets package within the R console
Install from CRAN:
install.packages("psychnets")

Install from Github:
library("remotes")
install_github("cran/psychnets")

Install by package version:
library("remotes")
install_version("psychnets", "0.5.2")



Attach the package and use:
library("psychnets")
Maintained by
Mohammed Saqr
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-07-30
Latest Update: 2026-07-30
Description:
Provides clean-room implementations for estimating psychometric network models, including correlation and partial-correlation networks, Gaussian graphical models with extended Bayesian information criterion (EBIC) regularization, nonparanormal and stepwise selection variants, information-filtering networks (the triangulated maximally filtered graph and the local-global inverse covariance), relative-importance networks, and Ising and mixed graphical models <doi:10.3758/s13428-017-0862-1> <doi:10.1007/978-3-031-54464-4_19>. All methods are implemented from first principles in base R without compiled dependencies and return consistent, tidy outputs. Functions are designed to be transparent and report optimization diagnostics where applicable. For Gaussian graphical models, the graphical lasso stationarity (Karush-Kuhn-Tucker) residual quantifies the deviation of the estimated solution from the optimum of the corresponding convex optimization problem.
How to cite:
Mohammed Saqr (2026). psychnets: Tidy Clean-Room Psychological Network Modeling. R package version 0.5.2, https://cran.r-project.org/web/packages/psychnets. Accessed 24 Oct. 2026.
Previous versions and publish date:
(2026-08-23 22:10), 0.4.3 (2026-07-30 19:20)
Other packages that cited psychnets R package
View psychnets citation profile
Other R packages that psychnets depends, imports, suggests or enhances
Complete documentation for psychnets
Functions, R codes and Examples using the psychnets R package
Full psychnets package functions and examples
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