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)
    <doi:10.1111/j.1468-0262.2004.00481.x> 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
NeedsCompilation: no
Packaged: 2026-03-21 13:00:44 UTC; Subir
Author: Subir Hait [aut, cre] (ORCID: <https://orcid.org/0009-0004-9871-9677>)
Maintainer: Subir Hait <haitsubi@msu.edu>
Repository: CRAN
Date/Publication: 2026-03-25 21:10:07 UTC
Built: R 4.6.0; ; 2026-04-26 06:20:48 UTC; unix
