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The role of causal criteria in causal inferences: Bradford Hill's "aspects of association"

Overview of attention for article published in Epidemiologic Perspectives & Innovations, June 2009
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)

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1 policy source
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4 X users
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3 Wikipedia pages

Citations

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73 Dimensions

Readers on

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127 Mendeley
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3 CiteULike
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Title
The role of causal criteria in causal inferences: Bradford Hill's "aspects of association"
Published in
Epidemiologic Perspectives & Innovations, June 2009
DOI 10.1186/1742-5573-6-2
Pubmed ID
Authors

Andrew C Ward

Abstract

As noted by Wesley Salmon and many others, causal concepts are ubiquitous in every branch of theoretical science, in the practical disciplines and in everyday life. In the theoretical and practical sciences especially, people often base claims about causal relations on applications of statistical methods to data. However, the source and type of data place important constraints on the choice of statistical methods as well as on the warrant attributed to the causal claims based on the use of such methods. For example, much of the data used by people interested in making causal claims come from non-experimental, observational studies in which random allocations to treatment and control groups are not present. Thus, one of the most important problems in the social and health sciences concerns making justified causal inferences using non-experimental, observational data. In this paper, I examine one method of justifying such inferences that is especially widespread in epidemiology and the health sciences generally - the use of causal criteria. I argue that while the use of causal criteria is not appropriate for either deductive or inductive inferences, they do have an important role to play in inferences to the best explanation. As such, causal criteria, exemplified by what Bradford Hill referred to as "aspects of [statistical] associations", have an indispensible part to play in the goal of making justified causal claims.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users 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 127 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 5%
United Kingdom 3 2%
Norway 1 <1%
Ireland 1 <1%
Spain 1 <1%
New Zealand 1 <1%
Unknown 114 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 18%
Researcher 20 16%
Student > Master 18 14%
Other 12 9%
Professor 10 8%
Other 33 26%
Unknown 11 9%
Readers by discipline Count As %
Medicine and Dentistry 52 41%
Psychology 9 7%
Social Sciences 8 6%
Agricultural and Biological Sciences 8 6%
Nursing and Health Professions 5 4%
Other 29 23%
Unknown 16 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 10 January 2024.
All research outputs
#4,547,718
of 24,870,516 outputs
Outputs from Epidemiologic Perspectives & Innovations
#12
of 35 outputs
Outputs of similar age
#18,992
of 116,851 outputs
Outputs of similar age from Epidemiologic Perspectives & Innovations
#1
of 1 outputs
Altmetric has tracked 24,870,516 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 35 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.6. This one scored the same or higher as 23 of them.
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 116,851 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
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