Arbeitspapier

"Randomisation bias" in the medical literature: A review

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.

Language
Englisch

Bibliographic citation
Series: IFS Working Papers ; No. W16/23

Classification
Wirtschaft
Methodological Issues: General
Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
Design of Experiments: General
Subject
clinical trials
social experiments
design of experiments
randomisation bias
sample selection
causal inference
treatment effects
external validity
generalizability

Event
Geistige Schöpfung
(who)
Sianesi, Barbara
Event
Veröffentlichung
(who)
Institute for Fiscal Studies (IFS)
(where)
London
(when)
2016

DOI
doi:10.1920/wp.ifs.2016.1623
Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Sianesi, Barbara
  • Institute for Fiscal Studies (IFS)

Time of origin

  • 2016

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