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Spatial analysis of cluster randomised trials: a systematic review of analysis methods

Overview of attention for article published in Emerging Themes in Epidemiology, September 2017
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  • Above-average Attention Score compared to outputs of the same age (62nd percentile)

Mentioned by

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5 tweeters

Citations

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3 Dimensions

Readers on

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24 Mendeley
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Title
Spatial analysis of cluster randomised trials: a systematic review of analysis methods
Published in
Emerging Themes in Epidemiology, September 2017
DOI 10.1186/s12982-017-0066-2
Pubmed ID
Authors

Christopher Jarvis, Gian Luca Di Tanna, Daniel Lewis, Neal Alexander, W. John Edmunds

Abstract

Cluster randomised trials (CRTs) often use geographical areas as the unit of randomisation, however explicit consideration of the location and spatial distribution of observations is rare. In many trials, the location of participants will have little importance, however in some, especially against infectious diseases, spillover effects due to participants being located close together may affect trial results. This review aims to identify spatial analysis methods used in CRTs and improve understanding of the impact of spatial effects on trial results. A systematic review of CRTs containing spatial methods, defined as a method that accounts for the structure, location, or relative distances between observations. We searched three sources: Ovid/Medline, Pubmed, and Web of Science databases. Spatial methods were categorised and details of the impact of spatial effects on trial results recorded. We identified ten papers which met the inclusion criteria, comprising thirteen trials. We found that existing approaches fell into two categories; spatial variables and spatial modelling. The spatial variable approach was most common and involved standard statistical analysis of distance measurements. Spatial modelling is a more sophisticated approach which incorporates the spatial structure of the data within a random effects model. Studies tended to demonstrate the importance of accounting for location and distribution of observations in estimating unbiased effects. There have been a few attempts to control and estimate spatial effects within the context of human CRTs, but our overall understanding is limited. Although spatial effects may bias trial results, their consideration was usually a supplementary, rather than primary analysis. Further work is required to evaluate and develop the spatial methodologies relevant to a range of CRTs.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 25%
Student > Master 3 13%
Student > Ph. D. Student 3 13%
Other 2 8%
Student > Bachelor 1 4%
Other 5 21%
Unknown 4 17%
Readers by discipline Count As %
Medicine and Dentistry 10 42%
Mathematics 3 13%
Immunology and Microbiology 2 8%
Agricultural and Biological Sciences 1 4%
Nursing and Health Professions 1 4%
Other 2 8%
Unknown 5 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 November 2018.
All research outputs
#4,182,048
of 13,903,017 outputs
Outputs from Emerging Themes in Epidemiology
#55
of 110 outputs
Outputs of similar age
#97,017
of 273,015 outputs
Outputs of similar age from Emerging Themes in Epidemiology
#1
of 1 outputs
Altmetric has tracked 13,903,017 research outputs across all sources so far. This one is in the 49th percentile – i.e., 49% of other outputs scored the same or lower than it.
So far Altmetric has tracked 110 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.1. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
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