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This package can be installed via devtools::install_github("cathyzzzhang/jointCompRisk") Meanwhile, there is also a dashboard version: https://ihpte0-wenqing-zhang.shinyapps.io/jointcompriskdash/

This package estimates the chance of each outcome over time (cumulative incidence functions) and performs joint inference so you can compare and combine outcomes instead of picking just one. It summarizes treatment benefit as restricted mean time gained for recovery (RMLT1) and restricted mean time lost to mortality (RMLT2), and also supports severity/quality-of-life weighted extensions (WRMLT1/WRMLT2). Results come with uncertainty intervals, plots, and reproducible examples (including COVID-19 trials)

Original work by Jiyang et al. was published in Biometrics, Volume 79, Issue 3, September 2023, Pages 1635–1645. https://academic.oup.com/biometrics/article/79/3/1635/7513812?login=false

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install.packages('jointCompRisk')

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142

Version

0.1.1

License

MIT + file LICENSE

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Maintainer

Wenqing Zhang

Last Published

October 20th, 2025

Functions in jointCompRisk (0.1.1)

prep_data_weighted_cif2

Prepare Data for Weighted CIF
prep_data_weighted_cif

Prepare Data for Weighted CIF (Legacy Wrapper)
main_df

Main Competing Risks Dataset Simulated clinical trial data with competing risks survival outcomes. This dataset follows the structure of Adaptive COVID-19 Treatment Trials (ACTT) with built-in treatment effects for demonstration purposes.
do_cif_analysis

Run Standard CIF Analysis
long_df

Longitudinal Severity Scores Dataset
do_weighted_cif_analysis

Run Weighted CIF Analysis
prep_data_cif

Prepare Data for Standard CIF
%>%

Pipe operator