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This function predicts item response probabilities and item responses using the item-focused tree model. The item-focused tree model combines logistic regression with recursive partitioning to detect Differential Item Functioning in dichotomous items. The model applies partitioning rules to the data, splitting it into homogeneous subgroups, and uses logistic regression within each subgroup to explain the data. Differential Item Functioning detection is achieved by examining potential group differences in item response patterns. This method is useful for understanding how different predictors, such as demographic or psychological factors, influence item responses across subgroups.
| Version: | 0.1.0 |
| Imports: | DIFtree |
| Suggests: | devtools, testthat (≥ 3.0.0) |
| Published: | 2025-02-13 |
| DOI: | 10.32614/CRAN.package.IFTPredictor |
| Author: | Muditha L. Bodawatte Gedara [aut, cre], Barret A. Monchka [aut], Lisa M. Lix [aut] |
| Maintainer: | Muditha L. Bodawatte Gedara <muditha.lakmali.1993 at gmail.com> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| CRAN checks: | IFTPredictor results |
| Reference manual: | IFTPredictor.pdf |
| Package source: | IFTPredictor_0.1.0.tar.gz |
| Windows binaries: | r-devel: IFTPredictor_0.1.0.zip, r-release: IFTPredictor_0.1.0.zip, r-oldrel: IFTPredictor_0.1.0.zip |
| macOS binaries: | r-devel (arm64): IFTPredictor_0.1.0.tgz, r-release (arm64): IFTPredictor_0.1.0.tgz, r-oldrel (arm64): IFTPredictor_0.1.0.tgz, r-devel (x86_64): IFTPredictor_0.1.0.tgz, r-release (x86_64): IFTPredictor_0.1.0.tgz, r-oldrel (x86_64): IFTPredictor_0.1.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.