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Observational studies are limited in that there could be an unmeasured variable related to both the response variable and the primary predictor. If this unmeasured variable were included in the analysis it would change the relationship (possibly changing the conclusions). Sensitivity analysis is a way to see how much of a relationship needs to exist with the unmeasured variable before the conclusions change. This package provides tools for doing a sensitivity analysis for regression (linear, logistic, and cox) style models.
| Version: | 1.4 |
| Published: | 2022-04-23 |
| DOI: | 10.32614/CRAN.package.obsSens |
| Author: | Greg Snow |
| Maintainer: | Greg Snow <538280 at gmail.com> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | obsSens results |
| Reference manual: | obsSens.pdf |
| Package source: | obsSens_1.4.tar.gz |
| Windows binaries: | r-devel: obsSens_1.4.zip, r-release: obsSens_1.4.zip, r-oldrel: obsSens_1.4.zip |
| macOS binaries: | r-release (arm64): obsSens_1.4.tgz, r-oldrel (arm64): obsSens_1.4.tgz, r-release (x86_64): obsSens_1.4.tgz, r-oldrel (x86_64): obsSens_1.4.tgz |
| Old sources: | obsSens archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.