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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 |
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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.