Package: jointCompRisk 0.1.0

jointCompRisk: Joint Inference for Competing Risks Data Using Multiple Endpoints

Tools for competing risks trials that allow simultaneous inference on recovery and mortality endpoints. Provides data preparation helpers, standard cumulative incidence estimators (restricted mean time gained/lost), and severity weighted extensions that integrate longitudinal ordinal outcomes to summarise treatment benefit. Methods follow Wen, Hu, and Wang (2023) Biometrics 79(3):1635-1645 <doi:10.1111/biom.13752>.

Authors:Wenqing Zhang [aut, cre], Jiyang Wen [aut], Chen Hu [aut], Meicheng Wang [aut]

jointCompRisk_0.1.0.tar.gz
jointCompRisk_0.1.0.zip(r-4.7)jointCompRisk_0.1.0.zip(r-4.6)jointCompRisk_0.1.0.zip(r-4.5)
jointCompRisk_0.1.0.tgz(r-4.6-any)jointCompRisk_0.1.0.tgz(r-4.5-any)
jointCompRisk_0.1.0.tar.gz(r-4.7-any)jointCompRisk_0.1.0.tar.gz(r-4.6-any)
jointCompRisk_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
jointCompRisk/json (API)

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

Bug tracker:https://github.com/cathyzzzhang/jointcomprisk/issues

Datasets:
  • long_df - Longitudinal Severity Scores Dataset
  • 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.

On CRAN:

Conda:

4.78 score 163 downloads 6 exports 18 dependencies

Last updated from:199273c90d. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK141
source / vignettesOK230
linux-release-x86_64OK130
macos-release-arm64OK134
macos-oldrel-arm64OK250
windows-develOK100
windows-releaseOK91
windows-oldrelOK90
wasm-releaseOK107

Exports:%>%do_cif_analysisdo_weighted_cif_analysisprep_data_cifprep_data_weighted_cifprep_data_weighted_cif2

Dependencies:clidplyrgenericsgluelatticelifecyclemagrittrMatrixpillarpkgconfigR6rlangsurvivaltibbletidyselectutf8vctrswithr

Competing Risks Survival Analysis with jointCompRisk
Introduction | Clinical Applications and Rationale | Theoretical Background | Cumulative Incidence Functions | Restricted Mean Survival Time | Endpoint-Specific Restricted Mean Times | Installation and Data Requirements | Load the sample data | Data Structure Requirements | For standard CIF analysis: your dataset needs: | For Severity-Weighted CIF Analysis, your dataset needs: | Part 1: Standard CIF Analysis: | Step 1: Data preparation | Step 2: Analysis | Step 3: Result Interpretation | Part 2: Weighted CIF Analysis: | Step 1: Data Preparation
Rendered fromVignette.Rmdusingknitr::rmarkdown

Last update: 2025-10-20
Started: 2025-06-29

Example Analysis using jointCompRisk
Part I: CIF Inference
Rendered fromExample_analysis.Rmdusingknitr::rmarkdown

Last update: 2025-10-08
Started: 2025-01-06