# ------------------------------------------------
# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# ------------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "oalasso" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'oalasso: Outcome-Adaptive Lasso Propensity Scores'
version: 1.0.0
doi: 10.32614/CRAN.package.oalasso
abstract: Estimates propensity scores by the outcome-adaptive lasso of Shortreed and
  Ertefaie (2017) <https://doi.org/10.1111/biom.12679> and the generalized outcome-adaptive
  lasso (GOAL) of Balde, Yang and Lefebvre (2023) <https://doi.org/10.1111/biom.13683>,
  using 'glmnet' with an exact penalty-scale correction so that the published objectives
  and tuning grids are reproduced. Tuning is by the weighted absolute mean difference
  balance criterion. The resulting score is designed to be supplied directly to the
  matchit() function of 'MatchIt' as a distance measure, to the weightit() function
  of 'WeightIt' as a propensity score, or to the psave() function of 'psAve' as an
  appended candidate.
authors:
- family-names: Kabata
  given-names: Daijiro
  email: daijiro.kabata@port.kobe-u.ac.jp
repository: https://kabajiro.r-universe.dev
repository-code: https://github.com/kabajiro/oalasso
commit: bc094196ca02e051fa09406e1a2d6e8e7b30a296
url: https://kabajiro.github.io/oalasso/
date-released: '2026-07-12'
contact:
- family-names: Kabata
  given-names: Daijiro
  email: daijiro.kabata@port.kobe-u.ac.jp