Package: WINS 1.5.1

WINS: The R WINS Package

Calculate the win statistics (win ratio, net benefit and win odds) for prioritized multiple endpoints, plot the win statistics and win proportions over study time if at least one time-to-event endpoint is analyzed, and simulate datasets with dependent endpoints. The package can handle any type of outcomes (continuous, ordinal, binary, time-to-event) and allow users to perform stratified analysis, inverse probability of censoring weighting (IPCW) and inverse probability of treatment weighting (IPTW) analysis.

Authors:Ying Cui [aut, cre], Bo Huang [aut]

WINS_1.5.1.tar.gz
WINS_1.5.1.zip(r-4.7)WINS_1.5.1.zip(r-4.6)WINS_1.5.1.zip(r-4.5)
WINS_1.5.1.tgz(r-4.6-any)WINS_1.5.1.tgz(r-4.5-any)
WINS_1.5.1.tar.gz(r-4.7-any)WINS_1.5.1.tar.gz(r-4.6-any)
WINS_1.5.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
WINS/json (API)

# Install 'WINS' in R:
install.packages('WINS', repos = c('https://cuiyingbeicheng.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • data_binary - An example with three binary endpoints.
  • data_continuous - An example with three continuous endpoints.
  • data_mix - An example with a mixture of endpoint types.
  • data_mix_stratum - An example with a mixture of endpoint types with three strata.
  • data_tte - An example with three TTE endpoints.
  • Z_t_con - Covariate history in the control group.
  • Z_t_trt - Covariate history in the treatment group.

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.85 score 6 scripts 280 downloads 7 mentions 5 exports 88 dependencies

Last updated from:6fec397f2a. Checks:7 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64WARNING156
source / vignettesOK287
linux-release-x86_64WARNING145
macos-release-arm64WARNING128
macos-oldrel-arm64WARNING126
windows-develWARNING109
windows-releaseWARNING82
windows-oldrelWARNING91
wasm-releaseOK126

Exports:partition_t.plotsim.datastat_t.plotwin.statwin.strategy.default

Dependencies:abindADGofTestbackportsbootbroomcarcarDatacliclustercolorspacecopulacorrplotcowplotcpp11DerivdoBydplyrfarverforecastFormulafracdiffgenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragslgtableisobandlabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmvtnormnlmenloptrnnetnumDerivpbkrtestpcaPPpillarpkgconfigplyrpolynompsplinepurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasreshape2rlangrstatixS7scalesSparseMstablediststringistringrsurvivaltibbletidyrtidyselecttimeDateurcautf8vctrsviridisviridisLitewithrzoo

Introduction to the R Package WINS

Ying Cui and Bo Huang^[Affiliation: Stanford University, Pfizer Inc.]

Rendered fromvignette.Rmdusingknitr::rmarkdownon May 28 2026.

Last update: 2025-05-05
Started: 2021-12-16