When Experiments Need Models
Keyword(s):
This paper argues that an important type of experiment-target inference, extrapolating causal effects, requires models to be successful. Focusing on extrapolation in Evidence-Based Policy, it is argued that extrapolation should be understood not as an inference from an experiment to a target directly, but as a hybrid inference that involves experiments and models. A general framework, METI, is proposed to capture this role of models, and several benefits are outlined: (1) METI highlights epistemically significant interactions between experiments and models, (2) reconciles some differences among existing accounts of experiment-target relationships, and (3) facilitates critical appraisal of inferential practices from experiments.
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2006 ◽
Vol 26
(4)
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pp. 329-337
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Keyword(s):
2015 ◽
Vol 15
(4)
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pp. 181-191
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2015 ◽
Vol 25
(5)
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pp. 360-365
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2011 ◽
Vol 3
(3)
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pp. 414-419
2010 ◽
Vol 15
(6)
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pp. 495-496
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