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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "SurrogateParadoxTest" in publications use:'
type: software
license: GPL-1.0-only
title: 'SurrogateParadoxTest: Empirical Testing of Surrogate Paradox Assumptions'
version: '2.2'
doi: 10.32614/CRAN.package.SurrogateParadoxTest
abstract: 'Provides functions to nonparametrically assess assumptions sufficient to
  prevent the surrogate paradox through hypothesis tests of stochastic dominance,
  monotonicity of conditional mean functions, and non-negative residual treatment
  effect. Details are described in: Hsiao E, Tian L, and Parast L (2026). "Avoiding
  the surrogate paradox: an empirical framework for assessing assumptions." Journal
  of Nonparametric Statistics <https://doi.org/10.1080/10485252.2025.2498609>. There
  are also functions to assess resilience to the surrogate paradox via calculation
  of the resilience probability, the resilience bound, and the resilience set. Details
  will be available in Hsiao E, Tian L, and Parast L, "Resilience Measures for the
  Surrogate Paradox" (Under Review). Lastly, there is a function to assess resilience
  to the surrogate paradox in the met-analytic setting, described in Hsiao E and Parast
  L, "A Functional-Class Meta-Analytic Framework for Quantifying Surrogate Resilience"
  (Under Review). A tutorial for this package can be found at <https://www.laylaparast.com/surrogateparadoxtest>.'
authors:
- family-names: Hsiao
  given-names: Emily
- family-names: Parast
  given-names: Layla
  email: parast@austin.utexas.edu
repository: https://laylaparast.r-universe.dev
commit: adb01716715d1990cf5d458438bee63d762ae4dd
date-released: '2026-04-11'
contact:
- family-names: Parast
  given-names: Layla
  email: parast@austin.utexas.edu