Sensitivity Analysis for Unmeasured Confounding in Longitudinal Studies
Overview
Evaluates the sensitivity of a given association to unmeasured confounding. The package consists of three functions. The first starts a 'shiny' app which assesses how strong a time-invariant confounder needs to be associated with the exposure and outcome to explain away a proposed causal association. The second and third functions simulate a time-dependent confounder over time either using a fit from the qmle() function from the 'yuima' package or directly using the observed effect estimate.
Install
Health
- OK13 OK2026-09-08
- ERROR12 OK, 1 ERROR2026-09-07
- OK8 OK2026-08-04
Documentation
- Help pages
- 8
- Examples that run
- 75%3 run in a plain check (1 of them under a condition) · 1 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 100%
- Documented parameters
- 87%
- Return-value docs
- 100%
- Help pages citing references
- 25%
- SDEconfounder PDF
Downloads
Dependencies
Code & Tests
Datasets
People & History
- 0.1.0Latest2026-08-03 · current release
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-08-03
- Total releases
- 1 / 1 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.5
- Bundled data
- 0.8 KB / 1 file
- Download size
- 628 KB
Cite
Cite this package
Run in R for the authors' entry:
citation("LongitudinalEvalue")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.
From data release v2026-10-20, which the citation names so these numbers can be found later. More on citing and the projects behind them.