On the use of nonparametric bounds for causal effects in null randomized trials

The goal of randomized experiments is to estimate the causal effect of an intervention on a clinically relevant outcome. When study subjects are missing outcome information due to factors related to the intervention, compliance, or the outcome, the causal effect is not identifiable from the observed data alone (1). When there is no missing data, randomization allows identification of the effect of assignment to the intervention, sometimes called the intent-to-treat effect; this is only equivalent to the intervention effect if subjects comply with their assigned intervention as directed. When this is not the case, the intervention effect is nonidentifiable, even with no missing data, without making additional assumptions (2).

Source: American Journal of Epidemiology - May 21, 2021 Category: Epidemiology Source Type: research