Package: wcox 1.0

wcox: Weights to Correct for Outcome Dependent Sampling in Time to Event Data

A new inverse probability of selection weighted Cox model to deal with outcome-dependent sampling in survival analysis.

Authors:Vera Arntzen [aut, cre], Mar Rodriguez-Girondo [aut]

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wcox.pdf |wcox.html✨
wcox/json (API)

# Install 'wcox' in R:
install.packages('wcox', repos = c('https://vharntzen.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/vharntzen/wcox/issues

Datasets:
  • fam_dat - Simulated time-to-event data.

On CRAN:

3.00 score 2 scripts 146 downloads 2 exports 24 dependencies

Last updated 2 years agofrom:9f42d5d8a9. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 15 2024
R-4.5-winNOTENov 15 2024
R-4.5-linuxNOTENov 15 2024
R-4.4-winNOTENov 15 2024
R-4.4-macNOTENov 15 2024
R-4.3-winNOTENov 15 2024
R-4.3-macNOTENov 15 2024

Exports:Calculate_weightsPrepare_data

Dependencies:clicpp11dplyrfansigenericsgluelatticelifecyclemagrittrMatrixpillarpkgconfigpurrrR6rlangstringistringrsurvivaltibbletidyrtidyselectutf8vctrswithr

Tutorial Inverse probability weights to correct for ascertainment bias using R package 'wcox'

Rendered fromTutorial_toy_data.Rmdusingknitr::rmarkdownon Nov 15 2024.

Last update: 2023-05-03
Started: 2021-05-31