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Matched case-control studies: a review of reported statistical methodology.

Overview of attention for article published in Clinical Epidemiology, May 2012
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

Mentioned by

twitter
1 tweeter
q&a
1 Q&A thread

Citations

dimensions_citation
64 Dimensions

Readers on

mendeley
218 Mendeley
citeulike
1 CiteULike
Title
Matched case-control studies: a review of reported statistical methodology.
Published in
Clinical Epidemiology, May 2012
DOI 10.2147/clep.s30816
Pubmed ID
Authors

Daniel Niven, Berthiaume, Fick, Laupland, Daniel J Niven, Luc R Berthiaume, Gordon H Fick, Kevin B Laupland

Abstract

Case-control studies are a common and efficient means of studying rare diseases or illnesses with long latency periods. Matching of cases and controls is frequently employed to control the effects of known potential confounding variables. The analysis of matched data requires specific statistical methods.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 218 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 <1%
United Kingdom 2 <1%
Peru 1 <1%
Austria 1 <1%
Canada 1 <1%
India 1 <1%
Iran, Islamic Republic of 1 <1%
Belgium 1 <1%
Denmark 1 <1%
Other 2 <1%
Unknown 205 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 52 24%
Student > Ph. D. Student 43 20%
Student > Master 43 20%
Student > Doctoral Student 14 6%
Student > Postgraduate 12 6%
Other 37 17%
Unknown 17 8%
Readers by discipline Count As %
Medicine and Dentistry 100 46%
Agricultural and Biological Sciences 17 8%
Psychology 11 5%
Mathematics 8 4%
Social Sciences 7 3%
Other 41 19%
Unknown 34 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 21 April 2015.
All research outputs
#3,219,009
of 12,073,561 outputs
Outputs from Clinical Epidemiology
#104
of 355 outputs
Outputs of similar age
#29,184
of 112,920 outputs
Outputs of similar age from Clinical Epidemiology
#5
of 24 outputs
Altmetric has tracked 12,073,561 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 355 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one has gotten more attention than average, scoring higher than 70% of its peers.
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 112,920 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.