How to design a randomized controlled experiment?

Randomized controlled experiments (RCTs) investigate cause-and-effect by randomly assigning participants to intervention or control groups. They establish causality by minimizing confounding variables through randomization. Key principles include generating a truly random allocation sequence and ensuring allocation concealment to prevent selection bias. Including a comparable control group (e.g., placebo or standard care) is essential to measure the intervention's net effect. Blinding participants and/or assessors, when feasible, reduces performance and detection bias. Adequate sample size calculation, based on the primary outcome, is critical for statistical power. RCTs are applicable across diverse fields like medicine, psychology, and economics, but require ethical approval and informed consent. Implementing an RCT involves several steps: first, define a clear research question and primary outcome. Second, identify the target population and establish eligibility criteria. Third, recruit participants and randomly assign them to groups using a reliable method (e.g., computer-generated random numbers). Fourth, deliver the intervention and control condition under standardized protocols. Fifth, measure outcomes consistently for all participants at predetermined timepoints. Finally, analyze results using appropriate statistical methods (e.g., intention-to-treat analysis) to determine efficacy. This process provides high-quality evidence for clinical and policy decisions.