Zaidi Jaffer M, VanderWeele Tyler J
Harvard University.
Stat Sin. 2021 Oct;31(4):2195-2212. doi: 10.5705/ss.202019.0207.
The sufficient cause model is extended from binary to categorical and ordinal outcomes to formalize the concept of sufficient cause interaction and synergism in this setting. This extension allows us to derive counterfactual and empirical conditions for detecting the presence of sufficient cause interactions for ordinal and categorical outcomes. Some of these conditions are entirely novel in that they cannot be derived from the sufficient cause model for binary outcomes. These empirical conditions enable researchers to determine whether two exposures display synergism for an ordinal or a categorical outcome. Likelihood ratio tests that use these derived empirical conditions are developed to infer sufficient cause interaction for ordinal and categorical outcomes. Lastly, we apply these likelihood ratio tests to detect sufficient cause interaction between two major resistance mutations in the development of HIV drug resistance to Etravirine.
充分病因模型从二元结局扩展到分类和有序结局，以在此背景下将充分病因相互作用和协同作用的概念形式化。这种扩展使我们能够推导出用于检测有序和分类结局中充分病因相互作用存在的反事实条件和实证条件。其中一些条件是全新的，因为它们无法从二元结局的充分病因模型中推导出来。这些实证条件使研究人员能够确定两种暴露因素对于有序或分类结局是否显示出协同作用。利用这些推导出来的实证条件开发似然比检验，以推断有序和分类结局中的充分病因相互作用。最后，我们应用这些似然比检验来检测在埃替拉韦耐药性发展过程中两种主要耐药突变之间的充分病因相互作用。
