Implements exact, normally approximated, and sampling-based sensitivity analysis for observational studies with contingency tables. Includes exact (kernel-based), normal approximation, and sequential importance sampling (SIS) methods using 'Rcpp' for computational efficiency. The methods build upon the framework introduced in Rosenbaum (2002) <doi:10.1007/978-1-4757-3692-2> and the generalized design sensitivity framework developed by Chiu (2025) <doi:10.48550/arXiv.2507.17207>.
| Version: | 0.1.5 |
| Imports: | Rcpp |
| LinkingTo: | Rcpp |
| Suggests: | rbounds |
| Published: | 2025-10-16 |
| DOI: | 10.32614/CRAN.package.sensitivityIxJ |
| Author: | Elaine Chiu [aut, cre] |
| Maintainer: | Elaine Chiu <kchiu4 at wisc.edu> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| CRAN checks: | sensitivityIxJ results |
| Reference manual: | sensitivityIxJ.html , sensitivityIxJ.pdf |
| Package source: | sensitivityIxJ_0.1.5.tar.gz |
| Windows binaries: | r-devel: sensitivityIxJ_0.1.5.zip, r-release: sensitivityIxJ_0.1.5.zip, r-oldrel: sensitivityIxJ_0.1.5.zip |
| macOS binaries: | r-release (arm64): sensitivityIxJ_0.1.5.tgz, r-oldrel (arm64): sensitivityIxJ_0.1.5.tgz, r-release (x86_64): sensitivityIxJ_0.1.5.tgz, r-oldrel (x86_64): sensitivityIxJ_0.1.5.tgz |
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