https://predicare1.r-universe.devRecent package updates in predicare1R-universehttps://github.com/predicare1.pnghttps://predicare1.r-universe.devWed, 01 Jul 2026 07:53:45 GMTolayinka.arimoro@ucalgary.ca (Olayinka I. Arimoro)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>.https://github.com/r-universe/predicare1/actions/runs/28511484574Wed, 01 Jul 2026 07:53:45 GMTgrmtree0.2.0successhttps://predicare1.r-universe.devhttps://github.com/predicare1/grmtreegetting-started-with-grmtree-package.Rmdgetting-started-with-grmtree-package.htmlGetting Started with the grmtree Package2025-08-19 21:21:022026-01-09 06:55:30GRMForest-implementation.RmdGRMForest-implementation.htmlGRM Forests for Robust DIF Detection2025-08-19 21:21:022026-01-09 06:55:30longitudinal-grmtree.Rmdlongitudinal-grmtree.htmlResponse Shift Detection with the Longitudinal GRMTree2026-07-01 07:39:332026-07-01 07:39:33