CNA Toppforsk-project
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Coincidence Analysis is a member of the family of聽configurational comparative methods聽(CCMs) of causal data analysis鈥攁lso known as聽set-theoretic听辞谤听叠辞辞濒别补苍听尘别迟丑辞诲蝉.聽Since the late 1980s CCMs聽have gradually been added to the methodological toolkit in disciplines as diverse as political science, sociology, business administration, management, environmental science, evaluation science, and public health. The most prominent CCM is Qualitative Comparative Analysis (QCA) (Ragin 2008). QCA, however, is unsuited to analyze causal structures with more than one endogenous variable, e.g. structures with common causes or causal chains. To overcome that restriction, Coincidence Analysis聽(CNA) has been first introduced in聽Baumgartner (,听). It has meanwhile been generalized in聽聽and is available as聽聽for the R environment聽.
This project has three objectives. The first is to fill all remaining gaps in the methodological protocol of CNA and to complement the CNA R-package accordingly. In particular, tools for robustness tests of CNA models and strategies for reducing model ambiguities shall be developed. The second objective is to systematically test the inferential potential of CNA by applying it to real-life studies from varying disciplines and, thereby, to explore the applicability of CNA outside of the standard domain of CCMs, for example, in biology, medicine or psychology. The third objective is to analyze the relationship between CNA and methods from other theoretical traditions鈥攊n particular Bayes-nets methods (cf. Spirtes et al. 2000; Pearl 2000) and regression-analytical methods (Gelman and Hill 2007). Are there substantive points of contact between these methodological traditions? Are there ways to fruitfully integrate them in multi-method studies? What are the conditions that determine what method is best suited to investigate a given phenomenon or to answer a given research question?