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• W3203343021 abstract "Configurational comparative methods (CCMs) and logic regression methods (LRMs) are two families of exploratory methods that employ very different techniques to analyze data generated by causal structures featuring conjunctural causation and equifinality. Aiming for the same by different means carries a substantive synergy potential, which, however, remains untapped so far because representatives of the two frameworks know little of each other. The purpose of this article is to change that. We first level the field for readers from both backgrounds by providing brief introductions to the basic ideas behind CCMs and LRMs. Then, we carve out the strengths and weaknesses of the two method families by benchmarking their performance when applied to binary data under a variety of different discovery contexts. It turns out that CCMs and LRMs have complementary strengths and weaknesses. This creates various promising avenues for cross-validation." @default.
• W3203343021 created "2021-10-11" @default.
• W3203343021 creator A5011340699 @default.
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• W3203343021 date "2021-10-01" @default.
• W3203343021 modified "2023-09-27" @default.
• W3203343021 title "Configurational Causal Modeling and Logic Regression" @default.
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• W3203343021 doi "https://doi.org/10.1080/00273171.2021.1971510" @default.
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