Package: modnets 0.9.0.9000

modnets: Modeling Moderated Networks

Methods for modeling moderator variables in cross-sectional, temporal, and multi-level networks. Includes model selection techniques and a variety of plotting functions. Implements the methods described by Swanson (2020) <https://www.proquest.com/openview/d151ab6b93ad47e3f0d5e59d7b6fd3d3>.

Authors:Trevor Swanson [aut, cre]

modnets_0.9.0.9000.tar.gz
modnets_0.9.0.9000.zip(r-4.7-any)modnets_0.9.0.9000.zip(r-4.6-any)modnets_0.9.0.9000.zip(r-4.5-any)
modnets_0.9.0.9000.tgz(r-4.6-any)modnets_0.9.0.9000.tgz(r-4.5-any)
modnets_0.9.0.9000.tar.gz(r-4.7-any)modnets_0.9.0.9000.tar.gz(r-4.6-any)
modnets_0.9.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
modnets/json (API)

# Install 'modnets' in R:
install.packages('modnets', repos = c('https://tswanson222.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/tswanson222/modnets/issues

Datasets:

On CRAN:

Conda:

2.70 score 1 stars 8 scripts 332 downloads 43 exports 128 dependencies

Last updated from:b118381885. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK220
source / vignettesOK206
linux-releaseOK201
macos-releaseOK159
macos-oldrelOK182
windows-develOK164
windows-releaseOK152
windows-oldrelOK161
wasm-releaseOK128

Exports:bootNetcentAutocentPlotcentTableclustAutoclustPlotclustTablecompareVARcondPlotcscoeffitNetworkgetFitCIsintsPlotlmerVARmlGVARmlGVARsimmnetPowerSimmodLLmodSelectmodTablenetnetIntsordinalizeplotBootplotCentralityplotCoefsplotModsplotNetplotNet2plotNet3plotPowerplotPvalsplotStabilitypredictNetresamplesampleSizeselectedsimNetSURfitSURllSURnetSURtablevarSelect

Dependencies:abindbackportsbase64encbootbroombslibcachemcarcarDatacheckmatecliclustercodetoolscolorspacecorpcorcowplotcpp11data.tableDerivdigestdoBydplyrevaluatefarverfastmapfdrtoolfontawesomeforeachforecastforeignFormulafracdifffsgenericsggplot2glassoglinternetglmnetglueGPArotationgridExtragtablegtoolshighrHmischtmlTablehtmltoolshtmlwidgetsigraphinteractionTestisobanditeratorsjpegjquerylibjsonliteknitrlabelinglatticelavaanleapslifecyclelme4lmerTestlmtestmagrittrMASSMatrixMatrixModelsmemoisemgcvmimeminqamnormtmodelrmvtnormnlmenloptrnnetnumDerivpbapplypbivnormpbkrtestpillarpkgconfigplyrpngpsychpurrrqgraphquadprogquantregR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasreshape2rlangrmarkdownrpartrstudioapiS7sandwichsassscalesshapeSparseMstringistringrsurvivalsystemfittibbletidyrtidyselecttimeDatetinytexurcautf8vctrsviridisLitewithrxfunyamlzoo

Readme and manuals

Help Manual

Help pageTopics
bfi databfiDat
Bootstrapping network estimation for moderated networksbootNet
Descriptive statistics for 'bootNet' objectsbootNetDescriptives cscoef summary.bootNet
Node centrality, clustering coefficients, and shortest path lengthscentAuto CentClust clustAuto
Create table of centrality values or clustering coefficientsCentralityAndClustering centTable clustTable
Plots for node centrality values or clustering coefficientscentPlot CentralityAndClusteringPlots clustPlot plotCentrality
Compare two to three 'lmerVAR' modelscompareVAR
Conditional effects plotcondPlot
Fit cross-sectional and idiographic moderated network modelsfitNetwork
Provides model coefficients with confidence intervalsgetFitCIs
Simulated GGM dataggmDat
Simulated temporal network datagvarDat
Plot confidence intervals for interaction termsintsPlot
Mixed-effects modeling for the GVAR in multilevel datalmerVAR
Log-likelihood functions and Likelihood Ratio Tests for moderated networksLogLikelihood modLL modTable SURll SURtable
Fit GVAR models with multilevel datamlGVAR
Simulated multi-level network datamlgvarDat
Main workhorse for simulating VAR and mlGVAR datamlGVARsim
Power simulator for cross-sectional and idiographic networksmnetPowerSim
modnets: Modeling Moderated Networksmodnets
Select a model based on output from 'resample'modSelect
Get adjacency matrices from fit objectsnet netInts
Convert continuous variables into ordinal variablesordinalize
Plot method for output of resample functionplot.resample
Plot 'bootNet' outputsplot.bootNet plotBoot
Plot model coefficients with confidence intervalsplotCoefs
Plot conditional networks at different levels of the moderatorplotMods
Plot moderated and unmoderated network modelsplot.ggm plot.ggmSim plot.GVARsim plot.lmerVAR plot.mlGVAR plot.mlGVARsim plot.SURnet plotNet
Plot temporal and contemporaneous networks in the same windowplotNet2
Plot temporal, contemporaneous, and between-subject networksplotNet3
Plot results of power simulationsplot.mnetPower plotPower
Plot the ECDF of p-values from resamplingplotPvals
Plot stability selection paths for a given outcomeplotStability
Calculate prediction error from network modelspredictNet
Bootstrapping or multi-sample splits for variable selectionresample
Reports the minimum sample size required to fit a network modelsampleSize
Shows which variables were selected for each node of a networkselected
Simulate network structure and datasimNet
Descriptive statistics for power simulation resultssummary.mnetPower
Fit SUR models with or without constraintsSURfit
Creates temporal and contemporaneous network of SUR resultsSURnet
Variable selection for moderated networksvarSelect