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cff-version: 1.2.0
message: 'To cite package "CausalSpline" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'CausalSpline: Nonlinear Causal Dose-Response Estimation via Splines'
version: 0.1.0
doi: 10.32614/CRAN.package.CausalSpline
abstract: '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) <https://doi.org/10.1111/j.1468-0262.2004.00481.x>
  for continuous treatments and extends it to fully nonparametric spline estimation.'
authors:
- family-names: Hait
  given-names: Subir
  email: haitsubi@msu.edu
  orcid: https://orcid.org/0009-0004-9871-9677
repository: https://causalfragility-lab.r-universe.dev
repository-code: https://github.com/causalfragility-lab/CausalSpline
commit: d3522dc0745e4a886b81b78e63b4ccc262c22da4
url: https://github.com/causalfragility-lab/CausalSpline
date-released: '2026-03-21'
contact:
- family-names: Hait
  given-names: Subir
  email: haitsubi@msu.edu
  orcid: https://orcid.org/0009-0004-9871-9677