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Clinical Infectious Diseases
Article . 2019 . Peer-reviewed
License: OUP Standard Publication Reuse
Data sources: Crossref
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How the Cluster-randomized Trial “Works”

Authors: James C Hurley;

How the Cluster-randomized Trial “Works”

Abstract

AbstractCluster-randomized trials (CRTs) are able to address research questions that randomized controlled trials (RCTs) of individual patients cannot answer. Of great interest for infectious disease physicians and infection control practitioners are research questions relating to the impact of interventions on infectious disease dynamics at the whole-of-population level. However, there are important conceptual differences between CRTs and RCTs relating to design, analysis, and inference. These differences can be illustrated by the adage “peas in a pod.” Does the question of interest relate to the “peas” (the individual patients) or the “pods” (the clusters)? Several examples of recent CRTs of community and intensive care unit infection prevention interventions are used to illustrate these key concepts. Examples of differences between the results of RCTs and CRTs on the same topic are given.

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Keywords

Intensive Care Units, Research Design, Physicians, Cluster Analysis, Humans, Communicable Diseases, Randomized Controlled Trials as Topic

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    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
30
Top 10%
Top 10%
Top 10%
hybrid