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The Virtues and Limitations of Randomized Experiments


Despite the consensus promoted by the evidence-based medicine framework, many authors continue to express doubts about the superiority of randomized controlled trials. This paper evaluates four objections targeting the legitimacy, feasibility, and extrapolation problems linked to the experimental practice of random allocation. I argue that random allocation is a methodologically sound and feasible practice contributing to the internal validity of controlled experiments dealing with heterogeneous populations. I emphasize, however, that random allocation is solely designed to ensure the validity of causal inferences at the level of groups. By itself, random allocation cannot enhance test precision, doesn’t contribute to external validity, and limits the applicability of causal claims to individuals.

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Fig. 1


  1. 1.

    For the purposes of the present discussion, we may treat the outcome “stress” as an operationalized variable and ignore issues related to its physical interpretation, such as the reality to which the variable ultimately refers and the extent to which the assessment method accurately measures this reality.

  2. 2.

    “One of the continuing appeals of deterministic methods for case study researchers is the power of the methods. For example, Mill’s Method of Difference can determine causality with only two observations. This power can only be obtained by assuming that the observation with the antecedent of interest, A, B, C and the one without, B, C are exactly alike except for the manipulation of A, and by assuming deterministic causation and the absence of measurement error and interactions among antecedents” (Sekhon 2008, 286–87).

  3. 3.

    Jaynes further generalizes the dilemma via an argument from infinite regression: “any specific experiment for which the existence of a physical probability is asserted is subject to physical analysis […] which will lead eventually to an understanding of its mechanism. But as soon as this understanding is reached, then this new experiment will also appear as an exceptional case […] where physical considerations obviate the usual postulates of physical probabilities” (2003, 324).

  4. 4.

    The intraclass correlation coefficient ρ is the ratio of between-group variance and total, within and between-group variance. Values of ρ range from 0, corresponding to no correlation of outcomes within a group (outcomes within and between the group are independent), to 1, corresponding to a situation when all individual outcomes within a cluster are identical (sample size is reduced to the number of clusters rather than the number of individuals). As ρ increases, the sample size required to detect a significant difference for the variable under investigation also increases.


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Baetu, T.M. The Virtues and Limitations of Randomized Experiments. Acta Anal (2021).

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