↓ Skip to main content

Combining directed acyclic graphs and the change-in-estimate procedure as a novel approach to adjustment-variable selection in epidemiology

Overview of attention for article published in BMC Medical Research Methodology, October 2012
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
2 tweeters

Citations

dimensions_citation
49 Dimensions

Readers on

mendeley
104 Mendeley
citeulike
1 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Combining directed acyclic graphs and the change-in-estimate procedure as a novel approach to adjustment-variable selection in epidemiology
Published in
BMC Medical Research Methodology, October 2012
DOI 10.1186/1471-2288-12-156
Pubmed ID
Authors

David Evans, Basile Chaix, Thierry Lobbedez, Christian Verger, Antoine Flahault

Abstract

Directed acyclic graphs (DAGs) are an effective means of presenting expert-knowledge assumptions when selecting adjustment variables in epidemiology, whereas the change-in-estimate procedure is a common statistics-based approach. As DAGs imply specific empirical relationships which can be explored by the change-in-estimate procedure, it should be possible to combine the two approaches. This paper proposes such an approach which aims to produce well-adjusted estimates for a given research question, based on plausible DAGs consistent with the data at hand, combining prior knowledge and standard regression methods.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 104 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 1 <1%
United Kingdom 1 <1%
Belgium 1 <1%
Spain 1 <1%
United States 1 <1%
Unknown 99 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 23%
Student > Master 14 13%
Researcher 12 12%
Other 11 11%
Professor > Associate Professor 7 7%
Other 16 15%
Unknown 20 19%
Readers by discipline Count As %
Medicine and Dentistry 35 34%
Agricultural and Biological Sciences 7 7%
Environmental Science 5 5%
Mathematics 4 4%
Veterinary Science and Veterinary Medicine 3 3%
Other 21 20%
Unknown 29 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 01 April 2019.
All research outputs
#8,404,022
of 14,574,683 outputs
Outputs from BMC Medical Research Methodology
#879
of 1,345 outputs
Outputs of similar age
#116,029
of 244,928 outputs
Outputs of similar age from BMC Medical Research Methodology
#1
of 1 outputs
Altmetric has tracked 14,574,683 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,345 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.6. This one is in the 31st percentile – i.e., 31% 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 244,928 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them