Correlation isn’t good enough: causal explanation and Big Data
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DOI: 10.1007/s11016-021-00625-4
Abstract: A review of Gary Smith and Jay Cordes: The Phantom Pattern Problem: The Mirage of Big Data. New York: Oxford University Press, 2020. read more here.
Keywords: enough causal; causal explanation; correlation good; good enough ... See more keywords
Missing data should be handled differently for prediction than for description or causal explanation.
Sign Up to like & getrecommendations! Published in 2020 at "Journal of clinical epidemiology"
DOI: 10.1016/j.jclinepi.2020.03.028
Abstract: Missing data is much studied in epidemiology and statistics. Theoretical development and application of methods for handling missing data have mostly been conducted in the context of prospective research data, and with a goal of… read more here.
Keywords: description causal; missing data; epidemiology; causal explanation ... See more keywords
Causation, complexity, and the Concert: the pragmatics of causal explanation in International Relations
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DOI: 10.1057/jird.2016.10
Abstract: A causal explanation provides information about the causal history of whatever is being explained. However, most causal histories extend back almost infinitely and can be described in almost infinite detail. Causal explanations therefore involve choices… read more here.
Keywords: causal explanations; causal explanation; causation complexity; international relations ... See more keywords
Rethinking causal explanation in interpretive international studies
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DOI: 10.1177/13540661211006454
Abstract: This article develops a model for causal explanations amenable to interpretive International Relations (IR) research. A growing field of scholars has turned toward causal inquiry while stressing the importance of shared understandings, identities, and social… read more here.
Keywords: causal explanations; causal; model; causal explanation ... See more keywords