Identifying Complex Causal Dependencies in Configurational Data with Coincidence Analysis

摘要

We present cna, a package for performing Coincidence Analysis (CNA). CNA is a configurational 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 themethod’s theoretical background and main algorithmic ideas, we demonstrate the use of the packageby means of an artificial and a real-life data set. Moreover, we outline planned enhancements of thepackage that will further increase its applicability