Provides comprehensive functionalities for causal modeling with Coincidence Analysis (CNA), which is a configurational comparative method of causal data analysis that was first introduced in Baumgartner (2009) <doi:10.1177/0049124109339369>, and generalized in Baumgartner & Ambuehl (2020) <doi:10.1017/psrm.2018.45>. CNA is designed to recover INUS-causation from data, which is particularly relevant for analyzing processes featuring conjunctural causation (component causation) and equifinality (alternative causation). CNA is currently the only method for INUS-discovery that allows for multiple effects (outcomes/endogenous factors), meaning it can analyze common-cause and causal chain structures. Moreover, as of version 4.0, it is the only method of its kind that provides measures for model evaluation and selection that are custom-made for the problem of INUS-discovery.
| Version: | 4.0.3 |
| Depends: | R (≥ 4.1.0) |
| Imports: | Rcpp, utils, stats, Matrix, matrixStats, car |
| LinkingTo: | Rcpp |
| Suggests: | dplyr, frscore, causalHyperGraph |
| Published: | 2025-06-02 |
| DOI: | 10.32614/CRAN.package.cna |
| Author: | Mathias Ambuehl [aut, cre, cph], Michael Baumgartner [aut, cph], Ruedi Epple [ctb], Veli-Pekka Parkkinen [ctb], Alrik Thiem [ctb] |
| Maintainer: | Mathias Ambuehl <mathias.ambuehl at consultag.ch> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://CRAN.R-project.org/package=cna |
| NeedsCompilation: | yes |
| Materials: | NEWS |
| In views: | CausalInference |
| CRAN checks: | cna results |
| Reference manual: | cna.html , cna.pdf |
| Vignettes: |
Introduction to the CNA method and package (source, R code) |
| Package source: | cna_4.0.3.tar.gz |
| Windows binaries: | r-devel: cna_4.0.3.zip, r-release: cna_4.0.3.zip, r-oldrel: cna_4.0.3.zip |
| macOS binaries: | r-release (arm64): cna_4.0.3.tgz, r-oldrel (arm64): cna_4.0.3.tgz, r-release (x86_64): cna_4.0.3.tgz, r-oldrel (x86_64): cna_4.0.3.tgz |
| Old sources: | cna archive |
| Reverse depends: | cnaOpt, frscore |
| Reverse imports: | causalHyperGraph |
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