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 (2018) <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.
Version: |
3.4.0 |
Depends: |
R (≥ 3.5.0) |
Imports: |
Rcpp, utils, stats, Matrix, matrixStats, car |
LinkingTo: |
Rcpp |
Suggests: |
dplyr |
Published: |
2022-07-08 |
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 |
Documentation:
Downloads:
Reverse dependencies:
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