因果推断:不同目标效应量及其可比性问题

Causal inference: different target effects and their comparability

因果推断是医学研究的主要目标之一,但由于缺乏对因果推断理论的深入认识,研究者为增强结果的可信性会盲目地采用多种统计方法对同一问题进行分析。这导致在比较和解释结果时出现较多问题。本文从因果推断反事实框架的潜在结果、因果效应和分配机制3个基本概念出发,解读因果推断中6个主要的效应量,并讨论不同情况下各效应量的可比性问题,以期望帮助研究者认识因果推断的原理,正确解读和比较研究结果以避免产生误导性的结论。

Causal inference is one of the main goals of medical research. However, due to the lack of an in-depth understanding of the theory of causal inference, researchers tend to blindly use multiple statistical methods to analyse the same question to enhance the credibility of the results, which leads to problems in interpretation of the analysis results.Based on the three basic concepts of potential outcomes, causal effects, and distributive mechanisms of the causal inference counterfactual framework, this paper introduced six main target effects in causal inference and discussed their comparability to help researchers understand the principle of causal inference and correctly interpret and compare research results to avoid misleading conclusions.