Package: grmtree 0.2.0

Olayinka I. Arimoro

grmtree: Recursive Partitioning for Graded Response Models

Provides methods for recursive partitioning based on the 'Graded Response Model' ('GRM'), extending the 'MOB' algorithm from the 'partykit' package. The package allows for fitting 'GRM' trees that partition the population into homogeneous subgroups based on item response patterns and covariates. Includes specialized plotting functions for visualizing 'GRM' trees with different terminal node displays (threshold regions, parameter profiles, and factor score distributions). The package also implements the Longitudinal GRMTree for detecting response shift in PROMs measured at two time points, embedding a constrained two-factor longitudinal GRM within recursive partitioning, with post-hoc characterization of recalibration and reprioritization. For more details on the methods, see Samejima (1969) <doi:10.1002/J.2333-8504.1968.TB00153.X>, Komboz et al. (2018) <doi:10.1177/0013164416664394> and Arimoro et al. (2025) <doi:10.1007/s11136-025-04018-6>.

Authors:Olayinka I. Arimoro [aut, cre], Tolulope T. Sajobi [aut], Lisa M. Lix [aut], Matthew T. James [ctb], Maria Santana [ctb], Emmanuel Ugochukwu [ctb]

grmtree_0.2.0.tar.gz
grmtree_0.2.0.zip(r-4.7)grmtree_0.2.0.zip(r-4.6)grmtree_0.2.0.zip(r-4.5)
grmtree_0.2.0.tgz(r-4.6-any)grmtree_0.2.0.tgz(r-4.5-any)
grmtree_0.2.0.tar.gz(r-4.7-any)grmtree_0.2.0.tar.gz(r-4.6-any)
grmtree_0.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
grmtree/json (API)

# Install 'grmtree' in R:
install.packages('grmtree', repos = c('https://predicare1.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/predicare1/grmtree/issues

Datasets:
  • grmtree_data - Medical Outcomes Study Social Support Survey (MOS-SS) Test Data
  • grmtree_long_data - Synthetic Longitudinal MOS-SS Social Support Survey Data

On CRAN:

Conda:

5.22 score 211 downloads 20 exports 93 dependencies

Last updated from:ecc763fb8d. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK300
source / vignettesOK316
linux-release-x86_64OK302
macos-release-arm64OK168
macos-oldrel-arm64OK302
windows-develOK205
windows-releaseOK224
windows-oldrelOK217
wasm-releaseOK185

Exports:discrpar_grmtreediscrpar_longitudinal_grmtreefscores_grmtreefscores_longitudinal_grmtreegenerate_node_scores_datasetgrmforestgrmforest.controlgrmtreegrmtree.controlitempar_grmtreeitempar_longitudinal_grmtreelatentpar_longitudinal_grmtreelongitudinal_grmtreeplot_rs_heatmapplot_rs_treeprepare_longitudinal_datars_characterizethreshpar_grmtreethreshpar_longitudinal_grmtreevarimp

Dependencies:audiobeeprbriocallrclassclicliprclustercodetoolscpp11crayondcurverDerivdescdiffobjdigestdplyre1071evaluatefarverFormulafsfuturefuture.applygenericsggplot2globalsglueGPArotationgridExtragtableinumisobandjsonlitelabelinglatticelibcoinlifecyclelistenvmagrittrMASSMatrixmgcvmiraimirtmvtnormnanonextnlmeotelparallellypartykitpbapplypermutepillarpkgbuildpkgconfigpkgloadpraiseprocessxprogressrproxypsqs2R.methodsS3R.ooR.utilsR6RColorBrewerRcppRcppArmadilloRcppParallelrlangrpartrprojrootS7sandwichscalessessioninfoSimDesignsplines2stringfishstrucchangesurvivaltestthattibbletidyselectutf8vctrsveganviridisLitewaldowithrzoo

Response Shift Detection with the Longitudinal GRMTree
Introduction | Install and load required packages | Import and explore the data | Prepare the longitudinal data | Phase 1: Fit the Longitudinal GRMTree | Phase 2: Characterize response shift | Accessing the results | Visualizing response shift | Extracting parameters and scores | Interpreting a tree with no split | Conclusion | References
Rendered fromlongitudinal-grmtree.Rmdusingknitr::rmarkdown

Last update: 2026-07-01
Started: 2026-07-01

Getting Started with the grmtree Package
Introduction | Install and Load required packages | Import and explore the data | IRT Assumptions: Check for unidimensionality assumption | Fit the graded response model (GRM) | Fit Indices for the GRM | Visualization: Visualize the results for all the items | Fit the tree-based graded response model (GRMTree) | Print the tree | Plot the GRMTree | Extract item parameters for terminal nodes | Conclusion
Rendered fromgetting-started-with-grmtree-package.Rmdusingknitr::rmarkdown

Last update: 2026-01-09
Started: 2025-08-19

GRM Forests for Robust DIF Detection
Introduction | Install and Load required packages | Import and prepare the data | GRM Forests Implementation | Define the forest control parameters | Grow the GRM Forest | Variable Importance | Compute the variable importance of each covariate | Plot the variable importance of each variable | Conclusion
Rendered fromGRMForest-implementation.Rmdusingknitr::rmarkdown

Last update: 2026-01-09
Started: 2025-08-19

Readme and manuals

Help Manual

Help pageTopics
Extract Discrimination Parameters from GRM Treediscrpar_grmtree
Extract Discrimination Parameters from Longitudinal GRM Treediscrpar_longitudinal_grmtree
Compute Latent Factor Scores for Each Terminal Node in a GRM Treefscores_grmtree
Compute Latent Factor Scores for Longitudinal GRM Treefscores_longitudinal_grmtree
Generate Dataset with Node Assignments and Factor Scoresgenerate_node_scores_dataset
Fit a Forest of Graded Response Model Trees for Ensemble-Based DIF Detectiongrmforest
Control Parameters for GRM Forestgrmforest.control
Fit a Graded Response Model Tree for Differential Item Functioning Detectiongrmtree
Medical Outcomes Study Social Support Survey (MOS-SS) Test Datagrmtree_data
Synthetic Longitudinal MOS-SS Social Support Survey Datagrmtree_long_data
Control Parameters for GRM Treesgrmtree.control
Extract Item Parameters from GRM Treeitempar_grmtree
Extract Item Parameters from Longitudinal GRM Treeitempar_longitudinal_grmtree
Extract Latent Trait Parameters from Longitudinal GRM Treelatentpar_longitudinal_grmtree
Fit a Longitudinal Graded Response Model Tree for Response Shift Detectionlongitudinal_grmtree
Plot Item-Level Response Shift Heatmapplot_rs_heatmap
Plot Response Shift Summary Treeplot_rs_tree
Plot Method for GRM Tree Objectsplot.grmtree
Plot Method for Longitudinal GRM Tree Objectsplot.longitudinal_grmtree
Plot Variable Importanceplot.varimp
Prepare Wide-Format Longitudinal PROM Dataprepare_longitudinal_data
Print Method for GRM Forestprint.grmforest
Print Method for GRM Tree Objectsprint.grmtree
Print Method for Response Shift Characterization Resultsprint.rs_characterization
Characterize Response Shift Within Terminal Nodes of a Longitudinal GRM Treers_characterize
Extract Threshold Parameters from GRM Treethreshpar_grmtree
Extract Threshold Parameters from Longitudinal GRM Treethreshpar_longitudinal_grmtree
Calculate Variable Importance for GRM Forestvarimp