Package: IFTPredictor
Type: Package
Title: Predictions Using Item-Focused Tree Models
Version: 0.1.0
Authors@R: c(person(given=c("Muditha","L."), 
                    family="Bodawatte Gedara", 
                    role=c("aut", "cre"),
                    email="muditha.lakmali.1993@gmail.com"),
             person(given=c("Barret","A."), 
                    family="Monchka", 
                    role="aut",
                    email="Barret.Monchka@umanitoba.ca"),
             person(given=c("Lisa","M."), 
                    family="Lix", 
                    role="aut",
                    email="Lisa.Lix@umanitoba.ca"))
Author: Muditha L. Bodawatte Gedara [aut, cre],
  Barret A. Monchka [aut],
  Lisa M. Lix [aut]
Maintainer: Muditha L. Bodawatte Gedara <muditha.lakmali.1993@gmail.com>
Description: 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.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: DIFtree
Suggests: devtools, testthat (>= 3.0.0)
RoxygenNote: 7.3.2
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2025-02-13 04:19:09 UTC; mudithalakmali
Repository: CRAN
Date/Publication: 2025-02-13 11:30:28 UTC
Built: R 4.6.0; ; 2026-04-26 03:55:29 UTC; unix
