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# CITATION 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 "syntheticdata" in publications use:'
type: software
license: MIT
title: 'syntheticdata: Synthetic Clinical Data Generation and Privacy-Preserving Validation'
version: 0.1.1
identifiers:
- type: doi
  value: 10.32614/CRAN.package.syntheticdata
abstract: Generates synthetic clinical datasets that preserve statistical properties
  while reducing re-identification risk. Implements Gaussian copula simulation, bootstrap
  with noise injection, and Laplace noise perturbation, with built-in utility and
  privacy validation metrics. Useful for privacy-aware data sharing in multi-site
  clinical research. Validates synthetic data quality via distributional similarity
  (Kolmogorov-Smirnov), discriminative accuracy (real-vs-synthetic classifier), and
  nearest-neighbor privacy ratio. Methods described in Jordon et al. (2022) <https://doi.org/10.48550/arXiv.2205.03257>
  and Snoke et al. (2018) <https://doi.org/10.1111/rssa.12358>.
authors:
- family-names: Gao
  given-names: Cuiwei
  email: 48gaocuiwei@gmail.com
preferred-citation:
  type: manual
  title: 'syntheticdata: Synthetic Clinical Data Generation and Privacy-Preserving
    Validation'
  authors:
  - family-names: Gao
    given-names: Cuiwei
    email: 48gaocuiwei@gmail.com
  year: '2026'
  notes: R package version 0.1.1
  url: https://github.com/CuiweiG/syntheticdata
repository: https://cuiweig.r-universe.dev
repository-code: https://github.com/CuiweiG/syntheticdata
commit: 24fa64a23f20a507a98846120c522f94efcc5b86
url: https://cuiweig.github.io/syntheticdata
date-released: '2026-04-19'
contact:
- family-names: Gao
  given-names: Cuiwei
  email: 48gaocuiwei@gmail.com