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.
| Version: |
0.1.0 |
| Depends: |
R (≥ 3.5) |
| Imports: |
ggplot2, yuima, methods, np, matrixStats, stats, rlang, zoo |
| Suggests: |
knitr, rmarkdown, shiny, bookdown |
| Published: |
2026-08-03 |
| DOI: |
10.32614/CRAN.package.LongitudinalEvalue (may not be active yet) |
| Author: |
Andreas Kristian Pedersen [aut, cre],
Anna Mejldal [ctb],
Afsaneh M. Nejad [ctb],
Kristian Debrabant [aut],
Sören Möller [aut] |
| Maintainer: |
Andreas Kristian Pedersen <andreaskpedersen at hotmail.com> |
| License: |
GPL-3 |
| URL: |
https://andreaskpedersen.shinyapps.io/LongitudinalEvalue/ |
| NeedsCompilation: |
no |
| Citation: |
LongitudinalEvalue citation info |
| CRAN checks: |
LongitudinalEvalue results |