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We present cna , a package for performing Coincidence Analysis (CNA). CNA is a cong-urational comparative method for the identication of complex causal dependencies—in particular,causal chains and common cause structures—in congurational data. After a brief introduction to themethod’s theoretical background and main algorithmic ideas, we demonstrate the use of the packageby means of an articial and a real-life data set. Moreover, we outline planned enhancements of thepackage that will further increase its applicability. Introduction Congurational comparative methods (CCMs) subsume techniques for the identication of complexcausal dependencies in congurational data using the theoretical framework of Boolean algebra andits various extensions (Rihoux and Ragin,2009). For example, Qualitative Comparative Analysis(QCA;Ragin,1987,2000,2008)—hitherto the most prominent representative of CCMs—has beenapplied in areas as diverse as business administration (e.g.,Chung,2001), environmental science(van Vliet et al.,2013), evaluation (Cragun et al.,2014), political science (Thiem,2011), public health(Longest and Thoits,2012) and sociology (Crowley,2013). Besides three stand-alone programs basedon graphical user interfaces, three R packages for QCA are currently available, each with a differentscope of functionality:

Identifying Complex Causal Dependencies in Configurational Data with Coincidence Analysis