Package: oalasso Type: Package Title: Outcome-Adaptive Lasso Propensity Scores Version: 1.0.0 Authors@R: person("Daijiro", "Kabata", email = "daijiro.kabata@port.kobe-u.ac.jp", role = c("aut", "cre", "cph")) Description: 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. Depends: R (>= 4.1) Imports: glmnet (>= 4.1-2), cobalt (>= 4.6.0), stats, utils, graphics Suggests: MatchIt, WeightIt, psAve, rpart, testthat (>= 3.0.0), knitr, rmarkdown VignetteBuilder: knitr Config/testthat/edition: 3 License: GPL (>= 2) URL: https://kabajiro.github.io/oalasso/, https://github.com/kabajiro/oalasso BugReports: https://github.com/kabajiro/oalasso/issues Encoding: UTF-8 Roxygen: list(markdown = TRUE) Config/roxygen2/version: 8.0.0 Repository: https://kabajiro.r-universe.dev Date/Publication: 2026-07-12 14:57:59 UTC RemoteUrl: https://github.com/kabajiro/oalasso RemoteRef: HEAD RemoteSha: bc094196ca02e051fa09406e1a2d6e8e7b30a296 NeedsCompilation: no Packaged: 2026-07-22 08:19:32 UTC; root Author: Daijiro Kabata [aut, cre, cph] Maintainer: Daijiro Kabata