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cff-version: 1.2.0
message: 'To cite package "IADT" in publications use:'
type: software
license: GPL-3.0-only
title: 'IADT: Interaction Difference Test for Prediction Models'
version: 1.2.1
doi: 10.32614/CRAN.package.IADT
abstract: Provides functions to conduct a model-agnostic asymptotic hypothesis test
  for the identification of interaction effects in black-box machine learning models.
  The null hypothesis assumes that a given set of covariates does not contribute to
  interaction effects in the prediction model. The test statistic is based on the
  difference of variances of partial dependence functions (Friedman (2008) <https://doi.org/10.1214/07-AOAS148>
  and Welchowski (2022) <https://doi.org/10.1007/s13253-021-00479-7>) with respect
  to the original black-box predictions and the predictions under the null hypothesis.
  The hypothesis test can be applied to any black-box prediction model, and the null
  hypothesis of the test can be flexibly specified according to the research question
  of interest. Furthermore, the test is computationally fast to apply as the null
  distribution does not require resampling or refitting black-box prediction models.
authors:
- family-names: Welchowski
  given-names: Thomas
  email: welchow@imbie.meb.uni-bonn.de
  orcid: https://orcid.org/0000-0003-2940-647X
repository: https://CRAN.R-project.org/package=IADT
date-released: '2024-05-14'
contact:
- family-names: Welchowski
  given-names: Thomas
  email: welchow@imbie.meb.uni-bonn.de
  orcid: https://orcid.org/0000-0003-2940-647X