Recursive Partitioning Based on Psychometric Models

Overview

Recursive partitioning based on psychometric models, employing the general MOB algorithm (from package partykit).

• Bradley-Terry trees (bttree): Strobl C, Wickelmaier F, Zeileis A (2011). “Accounting for Individual Differences in Bradley-Terry Models by Means of Recursive Partitioning.” Journal of Educational and Behavioral Statistics, 36(2), 135-153. doi:10.3102/1076998609359791
• Rasch trees (raschtree): Strobl C, Kopf J, Zeileis A (2015). “Rasch Trees: A New Method for Detecting Differential Item Functioning in the Rasch Model.” Psychometrika, 80(2), 289-316. doi:10.1007/s11336-013-9388-3
• Rating scale trees and partial credit trees (rstree/pctree): Komboz B, Zeileis A, Strobl C (2018). “Tree-Based Global Model Tests for Polytomous Rasch Models.” Educational and Psychological Measurement, 78(1), 128-166. doi:10.1177/0013164416664394
• MPT trees (mpttree): Wickelmaier F, Zeileis A (2018). “Using Recursive Partitioning to Account for Parameter Heterogeneity in Multinomial Processing Tree Models.” Behavior Research Methods, 50(3), 1217-1233. doi:10.3758/s13428-017-0937-z
• Parametric logisitic (n-PL) IRT model trees (npltree), including trees based on 1PL, 2PL, 3PL, and 4PL models.
• Generalized partial credit model trees (gpcmtree).

Installation

The stable version of psychotree is available from CRAN:

install.packages("psychotree")

The latest development version can be installed from R-universe:

install.packages("psychotree", repos = "https://zeileis.R-universe.dev")

License

The package is available under the General Public License version 3 or version 2