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# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "persuasio" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'persuasio: Causal Inference on Persuasion Effects'
version: 0.1.0
doi: 10.1086/724114
identifiers:
- type: doi
  value: 10.32614/CRAN.package.persuasio
abstract: Provides estimation and inference methods for causal persuasion rates in
  the potential-outcomes framework of Jun and Lee (2023, Journal of Political Economy)
  <https://doi.org/10.1086/724114>. The package computes bounds and confidence intervals
  for average and local persuasion rates under data scenarios with binary outcomes,
  treatments, and instruments, and also when only the outcome and instrument are observed.
  It also provides functions for calculating bounds from summary statistics.
authors:
- family-names: Chen
  given-names: Xinrui
  email: xc2731@columbia.edu
- family-names: Jun
  given-names: Sung Jae
  email: suj14@psu.edu
- family-names: Lee
  given-names: Sokbae
  email: sl3841@columbia.edu
preferred-citation:
  type: article
  title: Identifying the Effect of Persuasion
  authors:
  - family-names: Jun
    given-names: Sung Jae
    email: suj14@psu.edu
  - family-names: Lee
    given-names: Sokbae
    email: sl3841@columbia.edu
  journal: Journal of Political Economy
  year: '2023'
  volume: '131'
  issue: '8'
  doi: 10.1086/724114
  start: '2032'
  end: '2058'
repository: https://persuasio.r-universe.dev
repository-code: https://github.com/persuasio/persuasio-r
commit: 934c527622e6590fda6ca45d32450b326f091fa0
url: https://github.com/persuasio/persuasio-stata
date-released: '2026-07-27'
contact:
- family-names: Lee
  given-names: Sokbae
  email: sl3841@columbia.edu