cna: Causal Modeling with Coincidence Analysis (original) (raw)
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 |
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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: | |
In views: | CausalInference |
CRAN checks: | cna results |
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