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Dove Medical Press

Causal diagrams and the logic of matched case-control studies

Overview of attention for article published in Clinical Epidemiology, May 2012
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  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

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1 CiteULike
Title
Causal diagrams and the logic of matched case-control studies
Published in
Clinical Epidemiology, May 2012
DOI 10.2147/clep.s31271
Pubmed ID
Authors

Eyal Shahar, Shahar

Abstract

It is tempting to assume that confounding bias is eliminated by choosing controls that are identical to the cases on the matched confounder(s). We used causal diagrams to explain why such matching not only fails to remove confounding bias, but also adds colliding bias, and why both types of bias are removed by conditioning on the matched confounder(s). As in some publications, we trace the logic of matching to a possible tradeoff between effort and variance, not between effort and bias. Lastly, we explain why the analysis of a matched case-control study - regardless of the method of matching - is not conceptually different from that of an unmatched study.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
Canada 1 2%
Brazil 1 2%
Japan 1 2%
Spain 1 2%
Unknown 44 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 30%
Student > Ph. D. Student 7 14%
Professor 6 12%
Professor > Associate Professor 6 12%
Other 4 8%
Other 9 18%
Unknown 3 6%
Readers by discipline Count As %
Medicine and Dentistry 23 46%
Environmental Science 3 6%
Agricultural and Biological Sciences 3 6%
Nursing and Health Professions 2 4%
Biochemistry, Genetics and Molecular Biology 2 4%
Other 6 12%
Unknown 11 22%
Attention Score in Context

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 16 November 2021.
All research outputs
#7,414,686
of 22,671,366 outputs
Outputs from Clinical Epidemiology
#288
of 711 outputs
Outputs of similar age
#54,081
of 163,493 outputs
Outputs of similar age from Clinical Epidemiology
#3
of 7 outputs
Altmetric has tracked 22,671,366 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 711 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.8. This one has gotten more attention than average, scoring higher than 54% 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 163,493 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.