Identifying Complex Causal Dependencies in Configurational Data with Coincidence Analysis
Michael Baumgartner and Alrik Thiem
, The R Journal (2015) 7:1, pages 176-184.
Abstract We present cna, a package for performing Coincidence Analysis (CNA). CNA is a config urational comparative method for the identification of complex causal dependencies—in particular, causal chains and common cause structures—in configurational data. After a brief introduction to the method’s theoretical background and main algorithmic ideas, we demonstrate the use of the package by means of an artificial and a real-life data set. Moreover, we outline planned enhancements of the package that will further increase its applicability.
Received: 2014-12-17; online 2015-03-30@article{RJ-2015-014, author = {Michael Baumgartner and Alrik Thiem}, title = {{Identifying Complex Causal Dependencies in Configurational Data with Coincidence Analysis}}, year = {2015}, journal = {{The R Journal}}, doi = {10.32614/RJ-2015-014}, url = {https://doi.org/10.32614/RJ-2015-014}, pages = {176--184}, volume = {7}, number = {1} }