R: Modeling Moderated Networks

# Modeling Moderated Networks

## Documentation for package ‘modnets’ version 0.9.0

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

bfiDat | bfi data
bootNet | Bootstrapping network estimation for moderated networks
bootNetDescriptives | Descriptive statistics for 'bootNet' objects
centAuto | Node centrality, clustering coefficients, and shortest path lengths
CentClust | Node centrality, clustering coefficients, and shortest path lengths
centPlot | Plots for node centrality values or clustering coefficients
CentralityAndClustering | Create table of centrality values or clustering coefficients
CentralityAndClusteringPlots | Plots for node centrality values or clustering coefficients
centTable | Create table of centrality values or clustering coefficients
clustAuto | Node centrality, clustering coefficients, and shortest path lengths
clustPlot | Plots for node centrality values or clustering coefficients
clustTable | Create table of centrality values or clustering coefficients
compareVAR | Compare two to three 'lmerVAR' models
condPlot | Conditional effects plot
cscoef | Descriptive statistics for 'bootNet' objects
fitNetwork | Fit cross-sectional and idiographic moderated network models
getFitCIs | Provides model coefficients with confidence intervals
ggmDat | Simulated GGM data
gvarDat | Simulated temporal network data
intsPlot | Plot confidence intervals for interaction terms
lmerVAR | Mixed-effects modeling for the GVAR in multilevel data
LogLikelihood | Log-likelihood functions and Likelihood Ratio Tests for moderated networks
mlGVAR | Fit GVAR models with multilevel data
mlgvarDat | Simulated multi-level network data
mlGVARsim | Main workhorse for simulating VAR and mlGVAR data
mnetPowerSim | Power simulator for cross-sectional and idiographic networks
modLL | Log-likelihood functions and Likelihood Ratio Tests for moderated networks
modnets | modnets: Modeling Moderated Networks
modSelect | Select a model based on output from 'resample'
modTable | Log-likelihood functions and Likelihood Ratio Tests for moderated networks
net | Get adjacency matrices from fit objects
netInts | Get adjacency matrices from fit objects
ordinalize | Convert continuous variables into ordinal variables
plot.bootNet | Plot 'bootNet' outputs
plot.ggm | Plot moderated and unmoderated network models
plot.ggmSim | Plot moderated and unmoderated network models
plot.GVARsim | Plot moderated and unmoderated network models
plot.lmerVAR | Plot moderated and unmoderated network models
plot.mlGVAR | Plot moderated and unmoderated network models
plot.mlGVARsim | Plot moderated and unmoderated network models
plot.mnetPower | Plot results of power simulations
plot.resample | Plot method for output of resample function
plot.SURnet | Plot moderated and unmoderated network models
plotBoot | Plot 'bootNet' outputs
plotCentrality | Plots for node centrality values or clustering coefficients
plotCoefs | Plot model coefficients with confidence intervals
plotMods | Plot conditional networks at different levels of the moderator
plotNet | Plot moderated and unmoderated network models
plotNet2 | Plot temporal and contemporaneous networks in the same window
plotNet3 | Plot temporal, contemporaneous, and between-subject networks
plotPower | Plot results of power simulations
plotPvals | Plot the ECDF of p-values from resampling
plotStability | Plot stability selection paths for a given outcome
predictNet | Calculate prediction error from network models
resample | Bootstrapping or multi-sample splits for variable selection
sampleSize | Reports the minimum sample size required to fit a network model
selected | Shows which variables were selected for each node of a network
simNet | Simulate network structure and data
summary.bootNet | Descriptive statistics for 'bootNet' objects
summary.mnetPower | Descriptive statistics for power simulation results
SURfit | Fit SUR models with or without constraints
SURll | Log-likelihood functions and Likelihood Ratio Tests for moderated networks
SURnet | Creates temporal and contemporaneous network of SUR results
SURtable | Log-likelihood functions and Likelihood Ratio Tests for moderated networks
varSelect | Variable selection for moderated networks