Related Experiment Video
Updated: Sep 20, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Strengthening causal inference from randomised controlled trials of complex interventions
Jef L Leroy1, Edward A Frongillo2, Bezawit E Kase2
1Poverty, Health, and Nutrition Division, International Food Policy Research Institute, Washington, District of Columbia, USA j.leroy@cgiar.org.
Abstract:
Researchers conducting randomised controlled trials (RCTs) of complex interventions face design and analytical challenges that are not fully addressed in existing guidelines. Further guidance is needed to help ensure that these trials of complex interventions are conducted to the highest scientific standards while maximising the evidence that can be extracted from each trial. The key challenge is how to manage the multiplicity of outcomes required for the trial while minimising false positive and false negative findings. To address this challenge, we formulate three principles to conduct RCTs: (1) outcomes chosen should be driven by the intent and programme theory of the intervention and should thus be linked to testable hypotheses; (2) outcomes should be adequately powered and (3) researchers must be explicit and fully transparent about all outcomes and hypotheses before the trial is started and when the results are reported. Multiplicity in trials of complex interventions should be managed through careful planning and interpretation rather than through post hoc analytical adjustment. For trials of complex interventions, the distinction between primary and secondary outcomes as defined in current guidelines does not adequately protect against false positive and negative findings. Primary outcomes should be defined as outcomes that are relevant based on the intervention intent and programme theory, declared (ie, registered), and adequately powered. The possibility of confirmatory causal inference is limited to these outcomes. All other outcomes (either undeclared and/or inadequately powered) are secondary and inference relative to these outcomes will be exploratory.
More Related Videos
Related Concept Videos
Causality in Epidemiology
Strategies for Assessing and Addressing Confounding
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Randomized Experiments
Simple randomization
Simple...
What is an Experiment?
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Study Designs in Epidemiology
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...

