Logo image
On identification and estimation for sufficient cause interaction through a quasi-instrumental variable
期刊文章   同儕審查

On identification and estimation for sufficient cause interaction through a quasi-instrumental variable

Pei-Hsuan Hsia, An-Shun Tai, Shih-Chen Fu 和 Sheng-Hsuan Lin
Statistical methods in medical research, 卷.34(12), 頁碼.2237-2248
01/12/2025
PMID: 41026748
Web of Science ID: WOS:001584855000001

摘要

Health Care Sciences & Services Life Sciences & Biomedicine Mathematical & Computational Biology Mathematics Medical Informatics Physical Sciences Science & Technology Statistics & Probability
Mechanistic interaction concerns how exposures affect the outcome. When investigating mechanisms, synergism is the most mentioned type in the fields of genetic study and pharmacology. Synergism is defined under the framework of sufficient component cause model, which is difficult to be quantified directly. Sufficient cause interaction (SCI) is the only alternative metric to imply the existence of synergism. VanderWeele and Robins provided empirical tests for SCIs. However, this test only assesses the lower bound of SCIs rather than estimate SCIs directly due to the lack of the degree of freedom, which causes low power. To address this issue, in this study, we propose a novel method to estimate the probability of individual with SCI by introducing a new factor named quasi-instrumental variable, which is necessary for the background condition of SCI. We also develop a corresponding hypothesis test and show that it is more powerful than the existing empirical test. We demonstrate this method by applying it to estimate the synergistic effects between intestinal bacteria on the formation of Parkinson's disease.

檔案與連結 (1)

url
https://doi.org/10.1177/09622802251376236檢視
已出版(紀錄版本) 開放

相關連結

指標

1 檢視次數

詳細資料

Logo image