Estimating causal effects of internet interventions in the context of nonadherence.

ABSTRACT: 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 i

SUBMITTER: Hesser H 

PROVIDER: S-EPMC7495102 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature