期刊
BIOMETRIKA
卷 97, 期 1, 页码 123-132出版社
OXFORD UNIV PRESS
DOI: 10.1093/biomet/asp076
关键词
Causal risk difference; Causal risk ratio; Fractional programming; Linear programming; Potential response
资金
- Ministry of Education, Culture, Sports, Science and Technology of Japan
- JIST Foundation
- Mazda Foundation
Evaluating the causal effect of an exposure on a response from case-control and cohort studies is a major concern in epidemiological and medical research. Since causal effects are in general nonidentifiable from such studies, this paper derives bounds on two causal measures: the causal risk difference and the causal risk ratio. We use the potential response approach and a linear programming method to derive sharp bounds on the causal risk difference, and a novel fractional programming method to derive bounds on the causal risk ratio. In addition, in the presence of missing data, we consider three different missingness mechanisms and propose sharp bounds under these situations. The results provide new guidance on causal inference in case-control and cohort studies.
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