Purpose: There is more than one effect of a randomized intervention, and more than one response to a treatment. The mean group difference in the pre-specified outcome of a randomized controlled trial (RCT) estimates the average causal effect of treatment across causal mechanisms that may be distinct. To understand the comprehensive impact of an intervention, we propose identifying and separating the direct causal effects of the intervention from mediating, moderating, and modulating (individual differences) influences of uncontrolled variables.
Methods: Relational outcomes and moderated interventions describe two common mechanisms by which treatment interactions with uncontrolled variables expand or qualify the causal inferences to be drawn from an RCT, signifying treatment impact beyond that captured by conventional mean differences. Relational outcomes are associations between post-randomization measures. The treatment intervention may affect relational outcomes, and individual differences may modulate them. With moderated interventions, the effect of treatment on the outcome of interest depends on personal attributes or pre-randomization uncontrolled variables.
Results: Awareness and measurement of both types of mechanisms can greatly improve interpretation of the results of a clinical trial.
Conclusion: The integrated formal system of Dynamically Modified Outcomes (DYNAMO) provides comprehensive analysis of the diverse causal influences and interactions operating in a clinical trial.