threshpar_longitudinal_grmtree: Extract Threshold Parameters from Longitudinal GRM Tree

In grmtree: Recursive Partitioning for Graded Response Models

Extract Threshold Parameters from Longitudinal GRM Tree

Description

Extracts threshold (difficulty) parameters for each unique item from all terminal nodes of a longitudinal GRM tree. Only T1 item parameters are returned since the constrained model enforces equal thresholds across T1 and T2 within each node.

Usage

threshpar_longitudinal_grmtree(object, node = NULL, clean_names = TRUE, ...)

Arguments

object	A longitudinal_grmtree object.
node	Optional vector of node IDs. If NULL (default), extracts from all terminal nodes.
clean_names	Logical. If TRUE (default), clean item names by removing common prefixes (e.g., "resp_wideMOS_") and suffixes (e.g., "_BL", "_T1").
...	Additional arguments (currently unused).

Value

A data.frame with columns:

Node

Terminal node ID

Item

Item name (cleaned if clean_names = TRUE)

b1, b2, ..., bK

Threshold parameters for each category boundary

Contains n_items rows per node (not 2 * n_items).

See Also

longitudinal_grmtree for Phase 1 (tree fitting), discrpar_longitudinal_grmtree for extracting discrimination parameters for longitudinal GRMTree, itempar_longitudinal_grmtree for extracting item parameters for longitudinal GRMTree

Examples

library(grmtree)

# Load the synthetic longitudinal data
data("grmtree_long_data", package = "grmtree")

  # Prepare the wide-format response matrix
  items_t1 <- c("MOS_Listen", "MOS_Info", "MOS_Advice_Crisis", "MOS_Confide",
                "MOS_Advice_Want", "MOS_Fears", "MOS_Personal", "MOS_Understand")
  ld <- prepare_longitudinal_data(
    data = grmtree_long_data,
    items_t1 = items_t1,
    items_t2 = paste0(items_t1, "_year1"),
    covariates = c("sex", "age", "residency", "job",
                   "education", "comorbidity_count", "ever_smoker")
  )

  # Phase 1: fit the longitudinal GRM tree
  ltree <- longitudinal_grmtree(
    resp_wide ~ sex + age + residency + job +
      education + comorbidity_count + ever_smoker,
    data = ld, n_items = 8,
    control = grmtree.control(minbucket = 200)
  )

  # Print the threshold parameters
  thresholds <- threshpar_longitudinal_grmtree(ltree)
  print(thresholds)

  # Using the raw names
  threshpar_longitudinal_grmtree(ltree, clean_names = FALSE)  # raw names

grmtree documentation built on Sept. 2, 2026, 1:07 a.m.