Package: WINS 1.4.2

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_1.4.2.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'))

Peer review:

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.

3.32 score 6 scripts 651 downloads 7 mentions 5 exports 78 dependencies

Last updated 7 months agofrom:ddf5dfffd9. Checks:OK: 1 WARNING: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 27 2024
R-4.5-winWARNINGOct 27 2024
R-4.5-linuxWARNINGOct 27 2024
R-4.4-winWARNINGOct 27 2024
R-4.4-macWARNINGOct 27 2024
R-4.3-winWARNINGOct 27 2024
R-4.3-macWARNINGOct 27 2024

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

Dependencies:abindADGofTestbackportsbootbroomcarcarDataclicolorspacecopulacorrplotcowplotcpp11DerivdoBydplyrfansifarverFormulagenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragslgtableisobandlabelinglatticelifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellmvtnormnlmenloptrnnetnumDerivpbkrtestpcaPPpillarpkgconfigplyrpolynompsplinepurrrquantregR6RColorBrewerRcppRcppEigenreshape2rlangrstatixscalesSparseMstablediststringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisviridisLitewithr

Introduction to the R Package WINS

Rendered fromvignette.Rmdusingknitr::rmarkdownon Oct 27 2024.

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