QUANTITATIVE METHODS
1 Randomised Controlled Trials
Carlo Barone
Abstract
Randomised controlled trials (RCTs) aim at measuring the impact of a given intervention by comparing the outcomes of an experimental group (receiving the intervention) and a control group (not receiving it), to which individuals are randomly assigned. It is a useful quantitative method of ex ante evaluation, to test the impact of a program at a stage when it has not yet reached the totality of its target population (making the control group possible).
Keywords: Quantitative methods, experimental method, experimental/treatment and control groups, random assignment, treatment, contamination
I. What does this method consist of?
Randomised Controlled Trials (RCTs) assess the impact of a policy by comparing two groups: one of them is given access to the policy (experimental group), while the other is temporarily excluded from the policy (control group). The researcher translates the goals of the policy into quantitative outcomes measures and assesses the efficacy of the policy by measuring these outcomes across these two groups. If the experimental group displays better values on these outcome measures, we conclude that the policy is effective. However, this conclusion is valid if, and only if, we can assume that the two groups were perfectly equivalent. This is why the assignment to the two groups must be done randomly: if the sample is sufficiently large, the random assignment ensures that the two groups are, on average, initially equivalent on all characteristics, known or unknown by the researcher, measured or unmeasured in the evaluation study. Hence, any difference in the outcomes observed after the implementation of the policy can be interpreted as an impact of the policy.
When conducting an RCT, the researcher draws a sample of individuals and invites them to participate in the study, explaining that they may be assigned to either the experimental or the control group. Among the participants who have accepted to participate, half of them will be randomly assigned to the treatment and half to the control group. This 50%-50% ratio is the most common one because it results in more precise estimates than unbalanced ratios (e.g., 70%-30%). Before delivering the intervention, we may carry out a baseline measurement of the outcomes. This is not strictly necessary, but it is often done for several reasons, for instance because it allows the researcher to study the impacts of the treatment in a more dynamic way by comparing variations in the outcomes across the two groups.
While the randomisation is a necessary condition to make plausible causal claims when comparing the two groups, it is not a sufficient condition. In particular, the control group must remain excluded from the policy during the entire period of implementation of the policy, that is, we must avoid any form of treatment contamination. This implies, for instance, that individuals of the two groups do not communicat