Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/173957
Authors: 
Sianesi, Barbara
Year of Publication: 
2016
Series/Report no.: 
IFS Working Papers W16/23
Abstract: 
Randomised controlled or clinical trials (RCTs) are generally viewed as the most reliable method to draw causal inference as to the effects of a treatment, as they should guarantee that the individuals being compared differ only in terms of their exposure to the treatment of interest. This 'gold standard' result however hinges on the requirement that the randomisation device determines the random allocation of individuals to the treatment without affecting any other element of the causal model. This 'no randomisation bias' assumption is generally untestable but if violated would undermine the causal inference emerging from an RCT, both in terms of its internal validity and in terms of its relevance for policy purposes. This paper offers a concise review of how the medical literature identifies and deals with such issues.
Subjects: 
clinical trials
social experiments
design of experiments
randomisation bias
sample selection
causal inference
treatment effects
external validity
generalizability
JEL: 
C18
C21
C90
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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