Package: WINS 1.4.3

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_1.4.3.tar.gz
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WINS.pdf |WINS.html
WINS/json (API)

# Install 'WINS' in R:
install.packages('WINS', repos = c('https://cuiyingbeicheng.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • Z_t_con - Covariate history in the control group.
  • Z_t_trt - Covariate history in the treatment group.
  • 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.

On CRAN:

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

3.45 score 6 scripts 468 downloads 7 mentions 5 exports 81 dependencies

Last updated 1 months agofrom:d3ef106387. Checks:1 OK, 7 WARNING. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 12 2025
R-4.5-winWARNINGFeb 12 2025
R-4.5-macWARNINGFeb 12 2025
R-4.5-linuxWARNINGFeb 12 2025
R-4.4-winWARNINGFeb 12 2025
R-4.4-macWARNINGFeb 12 2025
R-4.3-winWARNINGFeb 12 2025
R-4.3-macWARNINGFeb 12 2025

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

Dependencies:abindADGofTestbackportsbootbroomcarcarDataclicolorspacecopulacorrplotcowplotcpp11DerivdoBydplyrfansifarverFormulagenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragslgtableisobandlabelinglatticelifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellmvtnormnlmenloptrnnetnumDerivpbkrtestpcaPPpillarpkgconfigplyrpolynompsplinepurrrquantregR6rbibutilsRColorBrewerRcppRcppEigenRdpackreformulasreshape2rlangrstatixscalesSparseMstablediststringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisviridisLitewithr

Introduction to the R Package WINS

Rendered fromvignette.Rmdusingknitr::rmarkdownon Feb 12 2025.

Last update: 2024-04-08
Started: 2021-12-16