tidyhte/CITATION.cff at main · ddimmery/tidyhte · GitHub

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cff-version: 1.2.0
message: "If you use this software, please cite it as below."
type: software
title: 'tidyhte: Tidy Estimation of Heterogeneous Treatment Effects'
version: 1.0.3
doi: 10.5281/zenodo.6325442
date-released: 2024-09-01
url: "https://github.com/ddimmery/tidyhte"
repository-code: "https://github.com/ddimmery/tidyhte"
authors:
  - family-names: "Dimmery"
    given-names: "Drew"
    orcid: "https://orcid.org/0000-0001-9602-6325"
    email: "cran@ddimmery.com"
abstract: >-
  Estimates heterogeneous treatment effects using tidy semantics
  on experimental or observational data. Methods are based on the
  doubly-robust learner of Kennedy (2023). You provide a simple
  recipe for what machine learning algorithms to use in estimating
  the nuisance functions and 'tidyhte' will take care of
  cross-validation, estimation, model selection, diagnostics and
  construction of relevant quantities of interest about the
  variability of treatment effects.
keywords:
  - R
  - causal inference
  - heterogeneous treatment effects
  - machine learning
  - experimental design
  - doubly-robust estimation
license: MIT
references:
  - type: article
    title: "Towards optimal doubly robust estimation of heterogeneous causal effects"
    authors:
      - family-names: "Kennedy"
        given-names: "Edward H."
    journal: "Electronic Journal of Statistics"
    volume: 17
    issue: 2
    year: 2023
    start: 3008
    end: 3049
    doi: "10.1214/23-EJS2157"