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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "winr" in publications use:'
type: software
license: MIT
title: 'winr: Randomization-Based Covariance Adjustment of Win Statistics'
version: 1.0.0
doi: 10.32614/CRAN.package.winr
abstract: 'A multi-visit clinical trial may collect participant responses on an ordinal
  scale and may utilize a stratified design, such as randomization within centers,
  to assess treatment efficacy across multiple visits. Baseline characteristics may
  be strongly associated with the outcome, and adjustment for them can improve power.
  The win ratio (ignores ties) and the win odds (accounts for ties) can be useful
  when analyzing these types of data from randomized controlled trials. This package
  provides straightforward functions for adjustment of the win ratio and win odds
  for stratification and baseline covariates, facilitating the comparison of test
  and control treatments in multi-visit clinical trials. For additional information
  concerning the methodologies and applied examples within this package, please refer
  to the following publications: 1. Weideman, A.M.K., Kowalewski, E.K., & Koch, G.G.
  (2024). “Randomization-based covariance adjustment of win ratios and win odds for
  randomized multi-visit studies with ordinal outcomes.” Journal of Statistical Research,
  58(1), 33–48. <https://doi.org/10.3329/jsr.v58i1.75411>. 2. Kowalewski, E.K., Weideman,
  A.M.K., & Koch, G.G. (2023). “SAS macro for randomization-based methods for covariance
  and stratified adjustment of win ratios and win odds for ordinal outcomes.” SESUG
  2023 Proceedings, Paper 139-2023.'
authors:
- family-names: Weideman
  given-names: Ann Marie K.
  email: anndo1@umbc.edu
- family-names: Kowalewski
  given-names: Elaine K.
- family-names: Koch
  given-names: Gary G.
repository: https://CRAN.R-project.org/package=winr
date-released: '2024-10-16'
contact:
- family-names: Weideman
  given-names: Ann Marie K.
  email: anndo1@umbc.edu