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Randomisation by cluster and the problem of social class bias

Bibliographic Data

ID11178708
AuthorsFE Alexander (University of Edinburgh), M M Roberts (University of Edinburgh), W Lutz (University of Edinburgh), W Hepburn (University of Edinburgh)
Year1989
Volume43
Issue1
Pages29-36
Publication date1989-03-01
Open AccessNo
TypeARTICLE
VenueJournal of Epidemiology and Community Health (JOURNAL)
Journal identifiersISSN: 0143-005X • E-ISSN: 1470-2738
PublisherBMJ (PUBLISHER • GB)
DOI10.1136/jech.43.1.29
PMID2592888
OpenAlexW2153831270
LanguageEN
References cited15

For randomised population trials the unit of randomisation is normally the individual person. In some situations, however, investigators take other groups as basic unit and one such design is cluster randomisation. Considerable attention has been given to this design recently in statistical and epidemiological literature. The Edinburgh randomised trial of breast cancer screening is an example which takes general practices as clusters of patients. The experience of this trial is reported here. Mortality from all causes, cardiovascular disease and lung cancer over the first 5 year period of follow up are examined. We found that spurious mortality differences were present in the analyses, which do not allow for socio-economic status. From examination of methods of adjusting for this, we conclude that allowance can be made at the analysis stage, and it is intended that this approach will be adopted when breast cancer mortality is analysed in the Edinburgh trial. Nevertheless, we recommend that for future studies with outcome related to socio-economic status, randomisations which use this design be stratified by socio-economic criteria where this is feasible

Allowance (engineering) · Breast cancer · Cancer · Cluster (spacecraft) · Cluster randomised controlled trial · Disease · Environmental health · Pathology · Population · Randomized controlled trial · Social class · Socioeconomic status · Spurious relationship · Statistics · Demography · Epidemiology · Health Systems, Economic Evaluations, Quality of Life · Medicine · Statistical Methods and Bayesian Inference · Statistical Methods in Clinical Trials · Surgery · Gerontology

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Highly citedNo

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