The case-crossover design (Maclure, 1991) is widely used in epidemiology and other fields to study causal effects of transient treatments on acute outcomes. However, its validity and causal interpretation have only been justified under informal conditions. Here, we place the design in a formal counterfactual framework for the first time. Doing so helps to clarify its assumptions and interpretation. In particular, when the treatment effect is non-null, we identify a previously unnoticed bias arising from common causes of the outcome at different person-times. We analytically characterize the direction and size of this bias and demonstrate its potential importance with a simulation. We also use our derivation of the limit of the case-crossover estimator to analyze its sensitivity to treatment effect heterogeneity, a violation of one of the informal criteria for validity. The upshot of this work for practitioners is that, while the case-crossover design can be useful for testing the causal null hypothesis in the presence of baseline confounders, extra caution is warranted when using the case-crossover design for point estimation of causal effects.
翻译:跨案设计(Maclure,1991年)在流行病学和其他领域被广泛使用,以研究转基因治疗对急性结果的因果关系;然而,其有效性和因果解释只在非正式条件下才有正当理由;在这里,我们首次将设计置于正式的反事实框架中;这样做有助于澄清其假设和解释;特别是,当治疗效果是非null时,我们发现由于不同人时的结果的共同原因而产生一种先前忽视的偏差;我们分析这种偏差的方向和大小,并通过模拟来表明其潜在重要性;我们还利用对转基因估计的推断来分析其对治疗效果异质的敏感性,这是对有效性非正式标准之一的违反;对从业者来说,这项工作的结果是,虽然转基因设计可以有助于检验存在基线构造者时的因果关系假设,但在使用转基因设计来估计因果关系时,必须格外谨慎。