grmtree (version 0.1.0)

generate_node_scores_dataset: Generate Combined Dataset with Node Assignments and Factor Scores

Description

Creates a dataset combining original data with node assignments and computed factor scores. Maintains original row order while adding node membership and factor score information.

Usage

generate_node_scores_dataset(grmtree_obj, method = "EAP")

Value

A data.frame containing: - Original variables from the model frame - 'node': Factor indicating terminal node membership (e.g., "Node 1") - 'factor_score': Computed latent factor scores Rows are in original order with sequential row names.

Arguments

grmtree_obj

A GRM tree object (from grmtree() function).

method

Scoring method to use: "EAP" (default), "MAP", "ML", or "WLE".

See Also

grmtree fits a Graded Response Model Tree, grmforest for GRM Forests, fscores_grmtree for computing factor scores, threshpar_grmtree for extracting threshold parameters, discrpar_grmtree for extracting discrimination parameters, itempar_grmtree for extracting item parameters

Examples

# \donttest{
  library(grmtree)
  library(hlt)
  data("asti", package = "hlt")
  asti$resp <- data.matrix(asti[, 1:4])

  # Fit GRM tree with gender and group as partitioning variables
  tree <- grmtree(resp ~ gender + group,
          data = asti,
          control = grmtree.control(minbucket = 30))

# Generate combined dataset
scored_data <- generate_node_scores_dataset(tree)

# Plot scores by node
boxplot(factor_score ~ node, data = scored_data)
# }