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: 3.0.1
Depends: R (≥ 3.2.0)
Imports: Rcpp, utils, stats, Matrix, matrixStats, car
LinkingTo: Rcpp
Suggests: dplyr
Published: 2020-11-06
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>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: NEWS
CRAN checks: cna results


Reference manual: cna.pdf
Vignettes: Introduction to the CNA method and package
Package source: cna_3.0.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: cna_3.0.1.tgz, r-oldrel: cna_3.0.1.tgz
Old sources: cna archive

Reverse dependencies:

Reverse depends: cnaOpt


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