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  "Package": "InterconectaR",
  "Version": "1.0.1",
  "Date": "2026-10-05",
  "Title": "Psychological Network Analysis and Psychometric Insights",
  "Encoding": "UTF-8",
  "Authors@R": "person(\"José\", \"Ventura-León\",\nemail = \"jventuraleon@gmail.com\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-2996-4244\"))",
  "Description": "Estimates psychological networks by group for research in\nthe social sciences and complements them with psychometric\nmodeling. It summarises centrality and bridge centrality\nindices, evaluates the stability of edges and centrality from\nbootstrap results, refines items by the stability of\nexploratory graph analysis (EGA), and plots networks with the\nvariance explained of each node. It also estimates an a priori\nsample size for EGA through Monte Carlo simulation and includes\nan interactive application to plan the sample size of a network\nstudy. Methods follow Epskamp, Borsboom and Fried (2018)\n<doi:10.3758/s13428-017-0862-1> and Golino and Epskamp (2017)\n<doi:10.1371/journal.pone.0174035>.",
  "License": "GPL (>= 3)",
  "URL": "https://github.com/jventural/InterconectaR",
  "BugReports": "https://github.com/jventural/InterconectaR/issues",
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  "Repository": "https://jventural.r-universe.dev",
  "Date/Publication": "2026-10-05 11:26:12 UTC",
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  "Author": "José Ventura-León [aut, cre] (ORCID:\n<https://orcid.org/0000-0003-2996-4244>)",
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  "_created": "2026-10-16T13:00:40.000Z",
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    "plot_net_group",
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    "qgraph_centrality_panel",
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    "run_EGA_combinations",
    "run_netpowerlab",
    "sample_size_EGA_control",
    "sample_size_EGA_montecarlo",
    "show_plots",
    "show_recommendation",
    "structure_groups",
    "summarise_case_drop_stability",
    "summarise_nonparametric_edges",
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      ]
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      "page": "calculate_centrality_sd_correlation",
      "title": "Centrality-SD Correlation",
      "topics": [
        "calculate_centrality_sd_correlation"
      ]
    },
    {
      "page": "centrality_bridge_plot",
      "title": "Bridge Centrality Plot",
      "topics": [
        "centrality_bridge_plot"
      ]
    },
    {
      "page": "centrality_bullet_plot",
      "title": "Bullet Chart para Indices de Centralidad",
      "topics": [
        "centrality_bullet_plot"
      ]
    },
    {
      "page": "centrality_cleveland_plot",
      "title": "Cleveland Dot Plot para Indices de Centralidad",
      "topics": [
        "centrality_cleveland_plot"
      ]
    },
    {
      "page": "centrality_duo_plot",
      "title": "Dual Centrality Plot",
      "topics": [
        "centrality_duo_plot"
      ]
    },
    {
      "page": "centrality_plots2",
      "title": "Centrality Plot (Version 2)",
      "topics": [
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    },
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      "title": "Choose Best Method",
      "topics": [
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      ]
    },
    {
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      "topics": [
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      ]
    },
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      "page": "combine_graphs_centrality2",
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    },
    {
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      "title": "Combine Group Plots",
      "topics": [
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    },
    {
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      "title": "Compute Network Scores",
      "topics": [
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    },
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      "title": "Convert EGA List to Data Frame",
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      "title": "Convert EGA Result to Data Frame",
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      "topics": [
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      ]
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      "page": "estimate_networks_by_group",
      "title": "Estimate Networks by Group",
      "topics": [
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    },
    {
      "page": "filter_correlation_stability",
      "title": "Filter Correlation Stability",
      "topics": [
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    {
      "page": "get_edge_weights_summary",
      "title": "Edge Weights Summary",
      "topics": [
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    },
    {
      "page": "make_likert_thresholds",
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      "topics": [
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    {
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      "title": "MGM Error Metrics",
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      "title": "Optimize Leiden Resolution",
      "topics": [
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      "title": "Plot Average TEFI by Sample Size",
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      "topics": [
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      "page": "plot_centrality_stability",
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      "topics": [
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    {
      "page": "plot_failure_decomposition",
      "title": "Plot Replication-Level Failure Decomposition Per Sample Size",
      "topics": [
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      ]
    },
    {
      "page": "plot_latent_network_diagram",
      "title": "Plot a latent network diagram (SEM path diagram)",
      "topics": [
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      ]
    },
    {
      "page": "plot_lvm",
      "title": "Plot Latent Variable Models",
      "topics": [
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      ]
    },
    {
      "page": "plot_net",
      "title": "Plot a single network with R2 progress rings",
      "topics": [
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    },
    {
      "page": "plot_net_group",
      "title": "Plot two networks side by side with R2 progress rings",
      "topics": [
        "plot_net_group"
      ]
    },
    {
      "page": "plot_networks_by_group",
      "title": "Plot networks by group as a combined panel",
      "topics": [
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    },
    {
      "page": "plot_performance_metrics",
      "title": "Plot Network Performance Metrics",
      "topics": [
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    },
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      "page": "plot_power_curve_ci",
      "title": "Plot the Power Curve with Bootstrap Confidence Band",
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    },
    {
      "page": "plot_sample_size_EGA_montecarlo",
      "title": "Plot Monte Carlo EGA Sample Size Results",
      "topics": [
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      ]
    },
    {
      "page": "print.sample_size_EGA_montecarlo",
      "title": "Narrative summary of a sample-size simulation",
      "topics": [
        "print.sample_size_EGA_montecarlo"
      ]
    },
    {
      "page": "print.scale_network_analysis",
      "title": "Print method for scale_network_analysis objects",
      "topics": [
        "print.scale_network_analysis"
      ]
    },
    {
      "page": "process_LCT",
      "title": "Process LCT (Loadings Comparison Test) results",
      "topics": [
        "process_LCT"
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    },
    {
      "page": "qgraph_centrality_panel",
      "title": "Create a combined panel with qgraph network and centrality plot",
      "topics": [
        "qgraph_centrality_panel"
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    },
    {
      "page": "refine_items_by_stability",
      "title": "Iteratively refine items by bootstrap stability",
      "topics": [
        "refine_items_by_stability"
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    },
    {
      "page": "run_EGA_combinations",
      "title": "Run EGA Combinations",
      "topics": [
        "run_EGA_combinations"
      ]
    },
    {
      "page": "run_netpowerlab",
      "title": "Launch the NetPowerLab Shiny Application",
      "topics": [
        "run_netpowerlab"
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    },
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      "page": "sample_size_EGA_control",
      "title": "Default control parameters for 'sample_size_EGA_montecarlo()'",
      "topics": [
        "sample_size_EGA_control"
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    },
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      "title": "A Priori Sample Size Estimation for EGA Using Monte Carlo Simulation",
      "topics": [
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    },
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      "title": "Visualize all plots stored in a 'sample_size_EGA_montecarlo' object",
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      "title": "Summarize Network Performance Metrics",
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