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cff-version: 1.2.0
message: 'To cite package "medshift" in publications use:'
type: software
license: MIT
title: 'medshift: Causal mediation analysis for stochastic interventions'
version: 0.1.4
abstract: Estimators of a parameter arising in the decomposition of the population
  intervention (in)direct effect of stochastic interventions in causal mediation analysis,
  including efficient one-step, targeted minimum loss (TML), re-weighting (IPW), and
  substitution estimators. The parameter estimated constitutes a part of each of the
  population intervention (in)direct effects. These estimators may be used in assessing
  population intervention (in)direct effects under stochastic treatment regimes, including
  incremental propensity score interventions and modified treatment policies. The
  methodology was first discussed by I Díaz and NS Hejazi (2020) <https://doi.org/10.1111/rssb.12362>.
authors:
- family-names: Hejazi
  given-names: Nima
  email: nh@nimahejazi.org
  orcid: https://orcid.org/0000-0002-7127-2789
- family-names: Díaz
  given-names: Iván
  email: ild2005@med.cornell.edu
  orcid: https://orcid.org/0000-0001-9056-2047
preferred-citation:
  type: manual
  title: 'medshift: Causal mediation analysis for stochastic interventions'
  authors:
  - family-names: Hejazi
    given-names: Nima S
  - family-names: Díaz
    given-names: Iván
    email: ild2005@med.cornell.edu
    orcid: https://orcid.org/0000-0001-9056-2047
  year: '2024'
  notes: R package version 0.1.4
  url: https://github.com/nhejazi/medshift
repository: https://nhejazi.r-universe.dev
repository-code: https://github.com/nhejazi/medshift
commit: 0ae0572fc5e37a8595b798909057afbc48304236
url: https://github.com/nhejazi/medshift
contact:
- family-names: Hejazi
  given-names: Nima
  email: nh@nimahejazi.org
  orcid: https://orcid.org/0000-0002-7127-2789
references:
- type: article
  title: Causal mediation analysis for stochastic interventions
  authors:
  - family-names: Díaz
    given-names: Iván
  - family-names: Hejazi
    given-names: Nima S
  journal: Journal of the Royal Statistical Society, Series B (Statistical Methodology)
  year: '2020'
  month: '2'
  doi: 10.1111/rssb.12362
  url: https://doi.org/10.1111/rssb.12362