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. Random-forest ensembles (`grmforest()`) with permutation variable importance are available for both the cross-sectional and longitudinal trees. 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>.

Package details

AuthorOlayinka I. Arimoro [aut, cre] (ORCID: <https://orcid.org/0009-0009-9464-589X>), Tolulope T. Sajobi [aut], Lisa M. Lix [aut], Matthew T. James [ctb], Maria Santana [ctb], Emmanuel Ugochukwu [ctb]
MaintainerOlayinka I. Arimoro <olayinka.arimoro@ucalgary.ca>
LicenseGPL-3
Version0.3.0
URL https://github.com/Predicare1/grmtree
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("grmtree")

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