Package index • psychnets

All functions

SRL_GPT SRL_Gemini SRL_Claude SRL_Mistral SRL_LLaMa: Self-regulated-learning (MSLQ) construct scores simulated by large language models
as.data.frame(<psychnet>): Tidy edge list for a psychnet network
as.data.frame(<psychnet_bootstrap>): Tidy a network bootstrap
casedrop_reliability(): Edge-weight stability coefficient (case-dropping subset bootstrap)
`$`(<psychnet>): Back-compatible field access for a psychnet object
certificate(): Correctness certificate of a fitted network
condition(): Condition a moderated network at a moderator value
cor_auto(): Automatic correlation matrix (polychoric / polyserial / Pearson)
cor_network(): Correlation network
dichotomize(): Dichotomize numeric columns to 0/1
difference_test(): Bootstrapped difference test for edges or centralities
ebic_glasso(): EBIC-regularized Gaussian graphical model (graphical lasso)
event_frequencies(): Action frequencies from an event log
ggm_modselect(): Stepwise Gaussian graphical model selection (ggmModSelect)
ggm_support_kkt(): Constrained Gaussian-MRF (graph-restricted MLE) stationarity residual
glasso_kkt(): Graphical-lasso stationarity (KKT) residual
glm_lasso_kkt(): Stationarity (KKT) residual of an L1-penalized GLM fit
huge_network(): Nonparanormal graphical model (huge)
ising_fit(): Ising network for binary data
ising_sampler(): Unregularized Ising network for binary data
lmg_certificate(): Relative-importance (LMG / Shapley) certificate
logo_network(): Local-Global sparse inverse covariance (LoGo)
mgm_fit(): Mixed graphical model
net_aggregate(): Aggregate a network's communities into super-nodes
net_boot(): Bootstrap a psychometric network
net_bridge(): Bridge centrality
net_centralities(): Node centrality
net_clustering(): Weighted clustering coefficients
net_compare(): Network Comparison Test
net_crosswalk(): Argument crosswalk: psychnet as a substitute for qgraph / IsingFit / mgm
net_edge_betweenness(): Edge betweenness centrality
net_predict(): Node predictability
net_smallworld(): Small-world index
net_stability(): Centrality-stability coefficient (case-dropping subset bootstrap)
network_reliability(): Split-half reliability of the network edge structure
node_predictability(): Node predictability as a plotting vector
pcor_network(): Partial correlation network
plot(<psychnet>): Plot a psychnet network
plot(<psychnet_bootstrap>): Plot a network bootstrap
plot(<psychnet_bridge>): Plot bridge centrality
plot(<psychnet_casedrop>): Plot edge-weight case-dropping stability
plot(<psychnet_centrality>): Plot node centralities
plot(<psychnet_difference>): Plot a bootstrapped difference test
plot(<psychnet_nct>): Plot a Network Comparison Test
plot(<psychnet_reliability>): Plot split-half reliability
plot(<psychnet_stability>): Plot centrality stability (case-dropping)
print(<psychnet>): Print a psychnet network
print(<psychnet_bootstrap>): Print a network bootstrap
print(<psychnet_casedrop>): Print an edge-weight stability result
print(<psychnet_group>) as.data.frame(<psychnet_group>) summary(<psychnet_group>): Per-group psychometric networks
print(<psychnet_moderated>): Print a moderated MGM fit
print(<psychnet_multilevel>) as.data.frame(<psychnet_multilevel>): Within / between event-data networks
print(<psychnet_nct>): Print a Network Comparison Test
print(<psychnet_redundancy>): Print a redundancy result
print(<psychnet_reliability>): Print a split-half reliability result
print(<psychnet_result_group>) as.data.frame(<psychnet_result_group>): Per-group framework results
print(<psychnet_stability>): Print a centrality-stability result
psychnet(): Estimate a psychometric network
redundancy(): Detect redundant node pairs ("goldbricker")
relimp_network(): Relative-importance network (LMG / Shapley)
summary(<psychnet>): Summarize a psychnet network
tmfg_certificate(): Structural certificate for a TMFG network
tmfg_network(): Triangulated Maximally Filtered Graph (TMFG)