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license: Artistic-2.0
title: 'combat.enigma: Fit and Apply ComBat, LMM, or Prescaling Harmonization for
  ENIGMA and Other Multisite MRI Data'
version: '1.1'
doi: 10.32614/CRAN.package.combat.enigma
abstract: Fit and apply ComBat, linear mixed-effects models (LMM), or prescaling to
  harmonize magnetic resonance imaging (MRI) data from different sites. Briefly, these
  methods remove differences between sites due to using different scanning devices,
  and LMM additionally tests linear hypotheses. As detailed in the manual, the original
  ComBat function was first modified for the harmonization of MRI data (Fortin et
  al. (2017) <https://doi.org/10.1016/j.neuroimage.2017.11.024>) and then modified
  again to create separate functions for fitting and applying the harmonization and
  allow missing values and constant rows for its use within the Enhancing Neuro Imaging
  Genetics through Meta-Analysis (ENIGMA) Consortium (Radua et al. (2020) <https://doi.org/10.1016/j.neuroimage.2017.11.024>);
  this package includes the latter version. LMM calls "lme" massively considering
  specific brain imaging details. Finally, prescaling is a good option for fMRI, where
  different devices can have varying units of measurement.
authors:
- family-names: Radua
  given-names: Joaquim
  email: quimradua@gmail.com
  orcid: https://orcid.org/0000-0003-1240-5438
repository: https://CRAN.R-project.org/package=combat.enigma
date-released: '2024-10-17'
contact:
- family-names: Radua
  given-names: Joaquim
  email: quimradua@gmail.com
  orcid: https://orcid.org/0000-0003-1240-5438