The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
Provides tools for integrated sensitivity analysis of evidence factors in observational studies. When an observational study allows for multiple independent or nearly independent inferences which, if vulnerable, are vulnerable to different biases, we have multiple evidence factors. This package provides methods that respect type I error rate control. Examples are provided of integrated evidence factors analysis in a longitudinal study with continuous outcome and in a case-control study. Karmakar, B., French, B., and Small, D. S. (2019)<doi:10.1093/biomet/asz003>.
Version: | 1.8 |
Imports: | sensitivitymv |
Published: | 2020-02-20 |
DOI: | 10.32614/CRAN.package.evidenceFactors |
Author: | Bikram Karmakar |
Maintainer: | Bikram Karmakar <bkarmakar at ufl.edu> |
License: | MIT + file LICENSE |
NeedsCompilation: | no |
CRAN checks: | evidenceFactors results |
Reference manual: | evidenceFactors.pdf |
Package source: | evidenceFactors_1.8.tar.gz |
Windows binaries: | r-devel: evidenceFactors_1.8.zip, r-release: evidenceFactors_1.8.zip, r-oldrel: evidenceFactors_1.8.zip |
macOS binaries: | r-release (arm64): evidenceFactors_1.8.tgz, r-oldrel (arm64): evidenceFactors_1.8.tgz, r-release (x86_64): evidenceFactors_1.8.tgz, r-oldrel (x86_64): evidenceFactors_1.8.tgz |
Old sources: | evidenceFactors archive |
Please use the canonical form https://CRAN.R-project.org/package=evidenceFactors to link to this page.
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.
Health stats visible at Monitor.