Package: cna
Type: Package
Title: Causal Modeling with Coincidence Analysis
Version: 2.2.0
Date: 2019-04-13
Authors@R: c(person("Mathias", "Ambuehl", role = c("aut", "cre", "cph"), 
                    email = "mathias.ambuehl@consultag.ch"),
             person("Michael", "Baumgartner", role = c("aut", "cph"),
                     email = "michael.baumgartner@unige.ch"),
             person("Ruedi", "Epple", role = "ctb"),
             person("Veli-Pekka", "Parkkinen", role = "ctb"),
             person("Alrik", "Thiem", role = "ctb")
             )
Description: 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 related to Qualitative Comparative Analysis (QCA), but contrary to the latter, it is custom-built for uncovering causal structures with multiple outcomes and it builds causal models from the bottom up by gradually combining single factors to complex dependency structures until the requested thresholds of model fit are met. The new functionalities provided by this package version include functions for evaluating and benchmarking the correctness of CNA's output, a function determining whether a solution is an INUS model, a function bringing non-INUS expressions into INUS form, and a function for identifying cyclic models. The package vignette has been updated accordingly.
License: GPL (>= 2)
URL: https://CRAN.R-project.org/package=cna
Depends: R (>= 3.2.0)
Imports: Rcpp, utils, stats, matrixStats
LinkingTo: Rcpp
Suggests: dplyr
NeedsCompilation: yes
LazyData: yes
Maintainer: Mathias Ambuehl <mathias.ambuehl@consultag.ch>
Packaged: 2019-04-13 10:34:30 UTC; MAM
Author: Mathias Ambuehl [aut, cre, cph],
  Michael Baumgartner [aut, cph],
  Ruedi Epple [ctb],
  Veli-Pekka Parkkinen [ctb],
  Alrik Thiem [ctb]
Repository: CRAN
Date/Publication: 2019-04-13 22:42:50 UTC
