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A poisson regression approach for modelling spatial autocorrelation between geographically referenced observations

Overview of attention for article published in BMC Medical Research Methodology, October 2011
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Title
A poisson regression approach for modelling spatial autocorrelation between geographically referenced observations
Published in
BMC Medical Research Methodology, October 2011
DOI 10.1186/1471-2288-11-133
Pubmed ID
Authors

Mohammadreza Mohebbi, Rory Wolfe, Damien Jolley

Abstract

Analytic methods commonly used in epidemiology do not account for spatial correlation between observations. In regression analyses, omission of that autocorrelation can bias parameter estimates and yield incorrect standard error estimates.

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 97 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 4%
New Zealand 1 1%
Belgium 1 1%
Unknown 91 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 23%
Researcher 14 14%
Student > Master 11 11%
Professor > Associate Professor 6 6%
Student > Bachelor 5 5%
Other 21 22%
Unknown 18 19%
Readers by discipline Count As %
Mathematics 13 13%
Environmental Science 12 12%
Social Sciences 10 10%
Agricultural and Biological Sciences 9 9%
Medicine and Dentistry 9 9%
Other 24 25%
Unknown 20 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 05 October 2011.
All research outputs
#15,236,094
of 22,653,392 outputs
Outputs from BMC Medical Research Methodology
#1,498
of 2,000 outputs
Outputs of similar age
#91,849
of 132,694 outputs
Outputs of similar age from BMC Medical Research Methodology
#9
of 17 outputs
Altmetric has tracked 22,653,392 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,000 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one is in the 16th percentile – i.e., 16% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 132,694 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.