# ------------------------------------------------ # 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 abstract: Estimates propensity scores by the outcome-adaptive lasso of Shortreed and Ertefaie (2017) and the generalized outcome-adaptive lasso (GOAL) of Balde, Yang and Lefebvre (2023) , 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://cran.r-universe.dev repository-code: https://github.com/kabajiro/oalasso commit: cf681fb970171c3b26df611ec9b5db68ca40719f url: https://kabajiro.github.io/oalasso/ date-released: '2026-07-21' contact: - family-names: Kabata given-names: Daijiro email: daijiro.kabata@port.kobe-u.ac.jp