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date: 14 December 2019

Abstract and Keywords

The article develops the notion of degree of causation, or effect size. It explores the extent to which mainstream social science methods—both quantitative and qualitative—succeed in establishing effect sizes. The article also describes the separate issue of explanandum-dependence, which is important to evaluating any cause's explanatory importance and yet has been comparatively neglected. Additionally, the regression coefficients and various nonprobabilistic qualitative definitions are explained. The article reports the specific issue of qualitative and quantitative approaches with partial explanations. Qualitative analysis is certainly capable of delivering causal strength (CS) scores, assuming that the causal structure has been identified correctly. Providing a formal analysis of explanatory strength (ES) proves an intricate business. Except in unusually favorable circumstances, regression coefficients do not track meaningful CS scores, even when the regression equation represents the causal structure truly.

Keywords: causation, effect size, social science, explanandum-dependence, regression coefficients, partial explanations, qualitative approach, quantitative approach, explanatory strength, causal strength

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