grmtree: Recursive Partitioning for Graded Response Models

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Authors: Olayinka I. Arimoro, Tolulope T. Sajobi, LM Lix
Cited by: 0
References: 4

Abstract

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). For more details on the methods, see Samejima (1969) , Komboz et al. (2018) and Arimoro et al. (2025) .

Fields of Study & Subjects

Psychometric Methodologies and Testing Statistical Methods and Bayesian Inference Educational Technology and Assessment

Publication details

Publication date
14 January 2026
Document type
Dataset