A substantial proportion of participants who are offered internet-based psychological treatments in randomized trials do not adhere and may therefore not receive treatment. Despite the availability of justified statistical methods for causal inference in such situations, researchers often rely on analytical strategies that either ignore adherence altogether or fail to provide causal estimands. The objective of this paper is to provide a gentle nontechnical introduction to complier average causal effect (CACE) analysis, which, under clear assumptions, can provide a causal estimate of the effect of treatment for a subsample of compliers. The article begins with a brief review of the potential outcome model for causal inference. After clarifying assumptions and model specifications for CACE in the latent variable framework, data from a previously published trial of an internet-based psychological treatment for irritable bowel syndrome are used to demonstrate CACE-analysis. Several model extensions are then briefly reviewed. The paper offers practical recommendations on how to analyze randomized trials of internet interventions in the context of nonadherence. It is argued that CACE-analysis, whenever it is considered appropriate, should be carried out as a complement to the standard intention-to-treat analysis and that the format of internet-based treatments is particularly well suited to such an analytical approach.

在随机试验中，有很大比例的接受基于互联网的心理治疗的参与者没有坚持，因此可能没有得到治疗。尽管在这种情况下可以使用合理的统计方法来进行因果推断，但研究人员经常依靠分析策略，要么完全忽略依从性，要么无法提供因果关系。本文的目的是为合规者平均因果效应（CACE）分析提供温和的非技术性介绍，在明确的假设下，它可以为合规者子样本提供治疗效果的因果估计。本文首先简要回顾了因果推理的潜在结果模型。在阐明了潜在变量框架中CACE的假设和模型规范后，来自先前发布的基于互联网的肠易激综合症心理治疗试验的数据用于证明CACE分析。然后简要回顾了几个模型扩展。本文提供了有关如何在不坚持的情况下分析互联网干预的随机试验的实用建议。有人认为，只要认为适当，就应进行CACE分析，作为对标准意向性治疗分析的补充，基于互联网的治疗形式特别适合这种分析方法。本文提供了有关如何在不坚持的情况下分析互联网干预的随机试验的实用建议。有人认为，只要认为适当，就应进行CACE分析，作为对标准意向性治疗分析的补充，基于互联网的治疗形式特别适合这种分析方法。本文提供了有关如何在不坚持的情况下分析互联网干预的随机试验的实用建议。有人认为，只要认为适当，就应进行CACE分析，作为对标准意向性治疗分析的补充，基于互联网的治疗形式特别适合这种分析方法。