Package: CausalSpline Type: Package Title: Nonlinear Causal Dose-Response Estimation via Splines Version: 0.1.0 Authors@R: person("Subir", "Hait", email = "haitsubi@msu.edu", role = c("aut", "cre"), comment = c(ORCID = "0009-0004-9871-9677")) Description: Estimates nonlinear causal dose-response functions for continuous treatments using spline-based methods under standard causal assumptions (unconfoundedness / ignorability). Implements three identification strategies: Inverse Probability Weighting (IPW) via the generalised propensity score (GPS), G-computation (outcome regression), and a doubly-robust combination. Natural cubic splines and B-splines are supported for both the exposure-response curve f(T) and the propensity nuisance model. Pointwise confidence bands are obtained via the sandwich estimator or nonparametric bootstrap. Also provides fragility diagnostics including pointwise curvature-based fragility, uncertainty-normalised fragility, and regional integration over user-defined treatment intervals. Builds on the framework of Hirano and Imbens (2004) for continuous treatments and extends it to fully nonparametric spline estimation. License: GPL (>= 3) Encoding: UTF-8 RoxygenNote: 7.3.3 Depends: R (>= 4.1.0) Imports: splines, stats, utils, ggplot2 (>= 3.4.0), sandwich, boot Suggests: testthat (>= 3.0.0), knitr, rmarkdown, patchwork, cobalt, dplyr VignetteBuilder: knitr Config/testthat/edition: 3 URL: https://github.com/causalfragility-lab/CausalSpline BugReports: https://github.com/causalfragility-lab/CausalSpline/issues Repository: https://causalfragility-lab.r-universe.dev Date/Publication: 2026-03-21 12:37:42 UTC RemoteUrl: https://github.com/causalfragility-lab/causalspline RemoteRef: HEAD RemoteSha: d3522dc0745e4a886b81b78e63b4ccc262c22da4 NeedsCompilation: no Packaged: 2026-07-03 19:09:03 UTC; root Author: Subir Hait [aut, cre] (ORCID: ) Maintainer: Subir Hait