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CausalSpline: Nonlinear Causal Dose-Response Estimation via Splines

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.

Version: 0.1.0
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
Published: 2026-03-25
DOI: 10.32614/CRAN.package.CausalSpline
Author: Subir Hait ORCID iD [aut, cre]
Maintainer: Subir Hait <haitsubi at msu.edu>
BugReports: https://github.com/causalfragility-lab/CausalSpline/issues
License: GPL (≥ 3)
URL: https://github.com/causalfragility-lab/CausalSpline
NeedsCompilation: no
Materials: README
CRAN checks: CausalSpline results

Documentation:

Reference manual: CausalSpline.html , CausalSpline.pdf
Vignettes: Introduction to CausalSpline (source, R code)

Downloads:

Package source: CausalSpline_0.1.0.tar.gz
Windows binaries: r-devel: CausalSpline_0.1.0.zip, r-release: CausalSpline_0.1.0.zip, r-oldrel: CausalSpline_0.1.0.zip
macOS binaries: r-release (arm64): CausalSpline_0.1.0.tgz, r-oldrel (arm64): not available, r-release (x86_64): CausalSpline_0.1.0.tgz, r-oldrel (x86_64): CausalSpline_0.1.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.