Empirical and counterfactual conditions for sufficient cause interactions

• 成果类型: Article
• 署名作者: Vanderweele, Tyler J.; Robins, James M.
• 署名单位: University of Chicago; Harvard University; Harvard T.H. Chan School of Public Health
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/asm090
• 发表日期: 2008
• 页码: 4961
• 关键词: regression; RISK; inference; ratios

摘要

Sufficient-component causes are discussed within the deterministic potential outcomes framework so as to formalize notions of sufficient causes, synergism and sufficient cause interactions. Doing so allows for the derivation of counterfactual and empirical conditions for detecting the presence of sufficient cause interactions. The conditions are novel in that, unlike other conditions in the literature, they make no assumption about monotonicity. The conditions can also be generalized and the conditions for three-way sufficient cause interactions are given explicitly. The statistical tests derived for sufficient cause interactions are compared with and contrasted to interaction terms in standard statistical models.