[aut,
cre]Basic sensitivity analysis of the observed relative risks adjusting for unmeasured confounding and misclassification of the exposure/outcome, or both. It follows the bias analysis methods and examples from the book by Lash T.L, Fox M.P, and Fink A.K. "Applying Quantitative Bias Analysis to Epidemiologic Data", ('Springer', 2009).
| Version: | 1.0.0 |
| Depends: | R (≥ 3.6.0), ggplot2 (≥ 3.3.3) |
| Imports: | triangle, trapezoid, actuar, dagitty, ggdag, boot, magrittr |
| Suggests: | testthat, knitr, rmarkdown, aplore3, directlabels, tidyverse, lattice, covr |
| Published: | 2021-02-23 |
| Author: | Denis Haine [aut,
cre] |
| Maintainer: | Denis Haine <denis.haine at gmail.com> |
| BugReports: | https://github.com/dhaine/episensr/issues |
| License: | GPL-2 |
| NeedsCompilation: | no |
| Citation: | episensr citation info |
| Materials: | README NEWS |
| CRAN checks: | episensr results |
| Reference manual: | episensr.pdf |
| Vignettes: |
Probabilistic Sensitivity Analysis Multiple Bias Modeling Additional Sensitivity Analyses Quantitative Bias Analysis for Epidemiologic Data |
| Package source: | episensr_1.0.0.tar.gz |
| Windows binaries: | r-devel: episensr_1.0.0.zip, r-release: episensr_1.0.0.zip, r-oldrel: episensr_1.0.0.zip |
| macOS binaries: | r-release: episensr_1.0.0.tgz, r-oldrel: episensr_0.9.6.tgz |
| Old sources: | episensr archive |
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