Run full pipeline for a single item type

Usage

run_pipeline_for_item_type(
  embedding_matrix,
  items,
  type_name,
  model = NULL,
  algorithm = "walktrap",
  uni.method = "louvain",
  corr = "auto",
  ncores = NULL,
  boot.iter = 500,
  uva.cut.off = 0.2,
  keep.org = FALSE,
  silently,
  plot
)

Arguments

embedding_matrix: Numeric matrix (columns = items for one type)
items: Data frame of items for this type (must include ID, statement, attribute)
type_name: Character. Type label used for tracking/logging.
model: NULL, "glasso", or "TMFG"
algorithm: EGA algorithm
uni.method: EGA uni.method
corr: Character. Correlation method. Default "auto" uses EGAnet's automatic detection.
ncores: Numeric. Number of cores for parallel processing. Default NULL uses EGAnet default.
boot.iter: Numeric. Number of bootstrap iterations. Default 500.
uva.cut.off: Numeric in [0, 1). wTO threshold for EGAnet::UVA. Default 0.20.
keep.org: Logical. Whether to include original items and embeddings
silently: Logical. Whether to print progress statements
plot: Logical. Whether to plot the network plots at the end

Value

A named list containing pipeline results for this type, including a filtering_audit table with one row per removed item and a reduction_summary table describing NMI and item-count changes by stage.