Abstract Details
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Activity Number:
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574
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Type:
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Contributed
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Date/Time:
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Wednesday, August 6, 2014 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics in Epidemiology
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Abstract #313689
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Title:
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Probabilities of Causation with Two Variables: Bounds and Sensitivity Analysis
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Author(s):
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Takahiro Hayashi*+ and Manabu Kuroki
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Companies:
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and Institute of Statistical Mathematics
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Keywords:
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causality ;
monotonicity ;
sufficient cause
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Abstract:
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We develop the probabilities of necessary or sufficient causation (or both) defined by Pearl (2009) to assess the interaction analyses with two factors. Pearl (2009) showed how to optimally bound the probabilities of causation using information from experimental and observational studies, with minimal assumptions concerning the data-generating process. We derive sharp bounds on the probabilities of causation with two variables using experimental or observational data (or both). In addition, we provide sensitivity analysis under monotonicity and exogeneity assumptions to assess the excess risk ratio with two variables. These results delineate precisely how empirical and observational data can be used in settling question of interaction.
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Authors who are presenting talks have a * after their name.
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