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flexCausal

0.1.0Package record

Causal Effect Estimation via Doubly Robust One-Step Estimators and TMLE in Graphical Models with Unmeasured Variables

0packages depend
2.7Kdownloads / year
64.2%test coverage
13/13flavors OK

Overview

About

Provides doubly robust one-step and targeted maximum likelihood (TMLE) estimators for average causal effects in acyclic directed mixed graphs (ADMGs) with unmeasured variables. Automatically determines whether the treatment effect is identified via backdoor adjustment or the extended front-door functional, and dispatches to the appropriate estimator. Supports incorporation of machine learning algorithms via 'SuperLearner' and cross-fitting for nuisance estimation. Methods are described in Guo and Nabi (2024) doi:10.48550/arXiv.2409.03962.

Changes in 0.1.0
  • Initial CRAN release providing doubly robust one-step and TMLE estimators for ADMGs with latent variables.
  • Bundled graph functions (make.graph(), f.parents(), etc.) to streamline identifiability checks.
  • Added simulated datasets (data_example_a, data_example_b, data_backdoor) to reproduce README/vignette examples.

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 2.3 min · r-release-macos-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK7 OK2026-03-30
Advisories

none known

Documentation

In release 0.1.0
READMEYes · 3,287 wordsVignettesYes · 1 · dynamicNEWSYes · 33% structured · mentions 0.1.0Citation fileYes · cites a publicationWebsitenot declared in DESCRIPTION
Help pages
20 (1 internal)
Examples that run
100%15 run in a plain check
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
20%
Vignettes (1)

Downloads

2.7K
CRAN downloads in the past year
Rank #10,367 · ~7/day · ~222/mo
Daily download trend is not available in this view yet.
36530 days
99090 days
2.7K1 year
Compare downloads with other packages →
Also on47 r2u7 autocran

Repository

11Stars
1Forks
0Open issues
0Open PRs
1Releases
99Commits
4Commit identities
License file reads as GPL-3.0 · 99 commits · Last activity 2026-03-19 · +10% stars, 30d
Responsiveness
not measured

Stars over time

2025-10-20 · 92026-09-26 · 11
PracticesBeta

2 development-tooling and community-health practices detected across 2 families in the upstream repository

Checks run against github.com/annaguo-bios/flexcausal on 2026-10-18.

Reproducibility and dev environment (1)
data-raw/
CRAN release process (1)
cran-comments.md
How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies
10 external dependencies (excludes base and recommended)

Installing flexCausal adds 29 packages (16 with compiled code, 18 MB of source tarballs). Heaviest: data.table 5.7 MB, gplots 4.6 MB, mvtnorm 1.0 MB.

Depends (1)
R >= 4.1
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (2)
Author, Maintainer since 0.1.0 (2026)
https://github.com/annaguo-bios
Releases (1)
  • R
    R 4.6.0 released · 2026-04-24
  • 0.1.0Latest
    2026-03-29 · current release
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2026-03-29
Total releases
1 / 1 yrs
License
GPL-3 OSI
Minimum R
≥ 4.1
Bundled data
258 KB / 4 files
Download size
4.5 MB

Cite

Cite this package

Run in R for the authors' entry:

citation("flexCausal")

The package provides a citation file, so citation() returns the authors' own entry.

Cite the R Observatory

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

APA

Balamuta, J. J. (2026). R Observatory: Metrics for flexCausal version 0.1.0 [Data set]. HJJB, LLC. Data release v2026-10-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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