R Observatory: Metrics for CoxAIPW version 0.0.3

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

CoxAIPW

0.0.3

Doubly Robust Inference for Cox Marginal Structural Model with Informative Censoring

0packages depend

2.5Kdownloads / year

–test coverage

13/13checks pass

Overview

About

Maintained by Jiyu LuoFirst published 2023-02-083 releasesCRAN page ↗GitHub ↗

Doubly robust estimation and inference of log hazard ratio under the Cox marginal structural model with informative censoring. An augmented inverse probability weighted estimator that involves 3 working models, one for conditional failure time T, one for conditional censoring time C and one for propensity score. Both models for T and C can depend on both a binary treatment A and additional baseline covariates Z, while the propensity score model only depends on Z. With the help of cross-fitting techniques, achieves the rate-doubly robust property that allows the use of most machine learning or non-parametric methods for all 3 working models, which are not permitted in classic inverse probability weighting or doubly robust estimators. When the proportional hazard assumption is violated, CoxAIPW estimates a causal estimated that is a weighted average of the time-varying log hazard ratio. Reference: Luo, J. (2023). Statistical Robustness - Distributed Linear Regression, Informative Censoring, Causal Inference, and Non-Proportional Hazards [Unpublished doctoral dissertation]. University of California San Diego.; Luo & Xu (2022) doi:10.48550/arXiv.2206.02296; Rava (2021) https://escholarship.org/uc/item/8h1846gs.

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("CoxAIPW", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("charlesluo1002/CoxAIPW")

Development version from charlesluo1002/CoxAIPW. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-coxaipw

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-CoxAIPW

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-CoxAIPW

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed).

Health

CRAN checks

13OK

Slowest check: 2.2 min · r-oldrel-windows-x86_64

Code health

None

Tests · ratio 0.00

not tracked

Coverage

100%

Documentation · exports

7

Dependencies · direct

Check history

OK2026-08-05
13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
NOTE2026-08-01
12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
OK2026-06-09
13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
ERROR2026-06-08
12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
OK2026-03-10
14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

READMEYes · 11 wordsVignettesNopkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo

Examples that run: 100%
Documented parameters: 100%
Return-value docs: 100%
References docs: 0%

Downloads

2.5K

CRAN downloads in the past year

Rank #16,309 · ~7/day · ~205/mo

Releases R versions

Daily download trend is not available in this view yet.

18730 days

66790 days

2.5K1 year

Compare downloads with other packages →

Also on107 r2u12 autocran

Repository

GitHub ↗ charlesluo1002/coxaipw

1Stars

0Forks

0Open issues

0Open PRs

0Releases

11Commits

5Contributors

11 commits · Last activity 2023-09-12

Stars over time

2024-07-27 · 12026-07-07 · 1

Repository practices

Upstream repositoryBeta

5 development-tooling and community-health practices detected across 3 families in the upstream repository

Checks run against github.com/charlesluo1002/coxaipw on 2026-08-23.

Continuous integration (2)

GitHub ActionsTravis CI

CRAN release process (2)

cran-comments.mdCRAN-SUBMISSION

Lint, format, editor (1)

RStudio project

How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies

6 external dependencies (excludes base and recommended)

Depends (0)

none

Imports (7)

survivalrandomForestSRC polspline tidyr ranger pracma gbm

LinkingTo (0)

none

Suggests (0)

none

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

Code & Tests

People & History

People (3)

Maintainer (1)

Jiyu Luo

Maintainer, Author

Authors (3)

Jiyu Luo

Maintainer, Author

Dennis Rava

Author

Ronghui Xu

Author

Package Timeline

3 releases. Pick two to compare their code metrics. R releases are shown for context.

R
R 4.6.0 released · 2026-04-24
R
R 4.5.0 released · 2025-04-11
R
R 4.4.0 released · 2024-04-24
0.0.3Latest
2023-09-20 · current release · diff ↗
0.0.2
2023-05-31 · diff ↗
R
R 4.3.0 released · 2023-04-21
0.0.1
2023-02-08
R
R 4.2.0 released · 2022-04-22

Package metadata

First published: 2023-02-08
Total releases: 3 / 3 yrs
License: GPL-3 OSI
Download size: 8.4 KB
Installed size: not tracked yet
With dependencies: not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("CoxAIPW")

Format

Luo, J., Rava, D., & Xu, R. (2023). CoxAIPW: Doubly Robust Inference for Cox Marginal Structural Model with Informative Censoring (Version 0.0.3) [Computer software]. https://doi.org/10.32614/CRAN.package.CoxAIPW

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for CoxAIPW version 0.0.3 [Data set]. HJJB, LLC. Data release v2026-08-23. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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