Publicación: Causality, Impartiality and Evidence-Based Policy
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2012-04-11
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Atribución-NoComercial-SinDerivadas 4.0 Internacional
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Randomisation, the assignment of experimental subjects to treatment groups by means of a random number generator, was first systematically applied in psychic research in the late nineteenth century and became popular in statistics after Ronald Fisher advocated its use in 1926 (Hacking 1988). In medicine and development economics, the two sciences we will focus on in this chapter, randomised trials are now widely regarded as the ‘gold standard’ of evidence. The overall aims of this chapter are to compare the use of randomised evaluations in these two sciences and to assess their ability to provide impartial evidence about causal claims. In short, we will argue that there are no good reasons to regard randomisation as a sine qua non for good evidential practice in either science. However, in medicine, but not in development economics, randomisation can provide impartiality from the point of view of regulatory agencies. The intuition is that if the available evidence leaves room for uncertainty about the effects of an intervention (such as a new drug), a regulator should make sure that such uncertainty cannot be exploited by some party’s private interest. We will argue that randomisation plays an important role in this context. By contrast, in the field evaluations that have recently become popular in development economics subjects have incentives to act strategically against the research protocol which undermines their use as neutral arbiter between conflicting parties.
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Categorías UNESCO
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clinical trials, field trials, impartiality
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Facultad de Filosofía
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Lógica, Historia y Filosofía de la Ciencia