cna: Causal Modeling with Coincidence Analysis
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: |
4.0.0 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
Rcpp, utils, stats, Matrix, matrixStats, car |
| LinkingTo: |
Rcpp |
| Suggests: |
dplyr, frscore, causalHyperGraph |
| Published: |
2025-04-04 |
| 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 |
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