Six‐way decomposition of causal effects: Unifying mediation and mechanistic interaction
學年 109
學期 1
出版（發表）日期 2020-11-30
作品名稱 Six‐way decomposition of causal effects: Unifying mediation and mechanistic interaction
作品名稱（其他語言）
著者 Yen‐Tsung Huang; An‐Shun Tai; Meng‐Ying Chou; Geng‐Xian Lin; Sheng‐Hsuan Lin
單位
出版者
著錄名稱、卷期、頁數 Statistics in Medicine 39(27), p.4051-4068
摘要 The sufficient component cause (SCC) model and counterfactual model are two common methods for causal inference, each with their own advantages: the SCC model allows the mechanistic interaction to be detailed, whereas the counterfactual model features a systemic framework for quantifying causal effects. Hence, integrating the SCC and counterfactual models may facilitate the conceptualization of causation. Based on the marginal SCC (mSCC) model, we propose a novel counterfactual mSCC framework that includes the steps of definition, identification, and estimation. We further propose a six‐way effect decomposition for assessing mediation and the mechanistic interaction. The results demonstrate that when all variables are binary, the six‐way decomposition is an extension of four‐way decomposition and that without agonism, the six‐way decomposition is reduced to four‐way decomposition. To illustrate the utility of the proposed decomposition, we apply it to a Taiwanese cohort to examine the mechanism of hepatitis C virus (HCV)‐induced hepatocellular carcinoma (HCC) with liver inflammation measured by alanine aminotransferase (ALT) as a mediator. Among the HCV‐induced HCC cases, 62.27% are not explained by either mediation or interaction in relation to ALT; 9.32% are purely mediated by ALT; 16.53% are caused by the synergistic effect of HCV and ALT; and 9.31% are due to the mediated synergistic effect of HCV and ALT. In summary, we introduce an SCC model framework based on counterfactual theory and detail the required identification assumptions and estimation procedures; we also propose a six‐way effect decomposition to unify mediation and mechanistic interaction analyses.
關鍵字 causal inference;effect decomposition;interaction;mediation;sufficient component cause
語言 en_US
ISSN 1097-0258
期刊性質 國外
收錄於 SCI
產學合作
通訊作者
審稿制度 是
國別 USA
公開徵稿
出版型式 ,電子版,紙本
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