Glossary
Randomized controlled trial
What is a randomized controlled trial?
A randomized controlled trial (RCT) is an experimental design that randomly assigns participants to treatment and control conditions to isolate the causal effect of an intervention. Proper randomization protects against systematic selection into treatment groups, making it a strong basis for causal inference.
How it works
Random assignment balances measured and unmeasured characteristics in expectation, but individual trials can have chance imbalances. Outcome differences must be interpreted with statistical uncertainty and possible bias from missing data, nonadherence, or measurement.
Key design elements include random allocation, blinding (participants and/or researchers do not know who received which treatment), control groups (no treatment, placebo, or active comparison), and adequate sample size (for statistical power).
RCTs are not always feasible (ethical constraints, practical limitations) or necessary (some questions do not require causal evidence).
Applied example
A company testing whether a new onboarding email sequence increases customer retention randomly assigns new customers to receive either the new sequence (treatment) or the existing one (control) and compares retention rates after 90 days. The randomized comparison estimates the effect of assignment to the sequence. A difference may still reflect chance, so the analysis should report its uncertainty and account for missing outcomes.
Why it matters
Well-run RCTs provide strong evidence for causal claims, and they must be complemented by other designs for questions where randomization is impractical or unethical.
Keep the assigned groups intact
In the onboarding example, suppose some customers never open their assigned emails. Removing them from the treatment group would change the question. People who open emails may already be more engaged, so a comparison restricted to openers would mix the effect of the sequence with the characteristics of its readers. An intention-to-treat analysis compares people according to their original assignment, estimating the effect of being assigned the new sequence under the conditions of the trial.
Missing retention records present a separate problem. “Include everyone assigned” is an analysis principle, not a way to know an unobserved outcome. Report how many outcomes are missing in each group and why, then assess how plausible missing-data assumptions change the result. A person who cancels and a person whose record is unavailable are not automatically the same outcome.
Allocation, concealment and blinding
Random allocation determines the group assignment. Allocation concealment prevents someone enrolling participants from knowing the next assignment in advance. Blinding concerns who knows the assignment afterward. These protect different parts of the study, as the CONSORT 2025 explanation describes. Customers may recognize the email they received, making participant blinding impractical; that does not stop a team from using an objective retention definition or hiding group labels from an analyst where feasible.
The J-PAL evaluation guide connects randomization to measurement, practical constraints and ethical design. An RCT still needs an intervention worth testing, a meaningful comparison and enough follow-up to answer the decision. A 90-day retention result does not establish one-year retention or a benefit to customers. Report the size of the difference, its uncertainty and any unwanted effects alongside the study label.