plot.longitudinal_grmtree: Plot Method for Longitudinal GRM Tree Objects

In grmtree: Recursive Partitioning for Graded Response Models

Plot Method for Longitudinal GRM Tree Objects

Description

Visualizes a longitudinal GRM tree with threshold region plots in terminal nodes. Unlike the cross-sectional plot.grmtree, this method displays only the unique item parameters (T1 items), since the constrained longitudinal model enforces equal parameters across T1 and T2 within each node.

Usage

## S3 method for class 'longitudinal_grmtree'
plot(
  x,
  type = "regions",
  tnex = 2L,
  drop_terminal = TRUE,
  names = FALSE,
  abbreviate = TRUE,
  ...
)

Arguments

x	A longitudinal_grmtree object.
type	Type of terminal node plot. Currently only "regions" is supported for the longitudinal model.
tnex	Numeric scaling factor for terminal node extension (default: 2).
drop_terminal	Logical indicating whether to drop terminal node IDs (default: TRUE).
names	Logical or character vector. If TRUE, use item names from the response matrix. If a character vector, use as custom labels. If FALSE (default), use numeric indices 1 through n_items.
abbreviate	Logical or numeric. If TRUE, abbreviate item names. If numeric, abbreviate to that many characters.
...	Additional arguments passed to the terminal panel function.

Details

The region plot displays threshold parameters as colored horizontal bands for each item within each terminal node. Darker shading represents lower response categories and lighter shading represents higher categories. The height of each band corresponds to the range of the latent trait over which that response category is most likely.

Because the constrained longitudinal GRM enforces a_{m,T1} = a_{m,T2} and b_{k,m,T1} = b_{k,m,T2}, the T1 and T2 item parameters are identical. The plot therefore shows only the n_items unique items rather than all 2 * n_items columns in the response matrix.

Value

Invisibly returns the tree object. Called for its side effect of producing a plot.

See Also

longitudinal_grmtree for fitting the tree, plot.grmtree for cross-sectional tree plots

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)
  )

  # Region plot with numeric labels
  plot(ltree)

  # Region plot with item names
  plot(ltree, names = TRUE)

  # Custom labels
  plot(ltree, names = c("Listen", "Info", "Crisis",
    "Confide", "Advice", "Fears", "Personal", "Understand"))

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