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Twitter Demographics
Mendeley readers
Attention Score in Context
| Title |
A counterfactual approach to bias and effect modification in terms of response types
|
|---|---|
| Published in |
BMC Medical Research Methodology, July 2013
|
| DOI | 10.1186/1471-2288-13-101 |
| Pubmed ID | |
| Authors |
Etsuji Suzuki, Toshiharu Mitsuhashi, Toshihide Tsuda, Eiji Yamamoto |
| Abstract |
The counterfactual approach provides a clear and coherent framework to think about a variety of important concepts related to causation. Meanwhile, directed acyclic graphs have been used as causal diagrams in epidemiologic research to visually summarize hypothetical relations among variables of interest, providing a clear understanding of underlying causal structures of bias and effect modification. In this study, the authors aim to further clarify the concepts of bias (confounding bias and selection bias) and effect modification in the counterfactual framework. |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Belgium | 1 | 2% |
| Unknown | 47 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 29% |
| Researcher | 5 | 10% |
| Professor | 5 | 10% |
| Student > Master | 5 | 10% |
| Professor > Associate Professor | 3 | 6% |
| Other | 9 | 19% |
| Unknown | 7 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 17 | 35% |
| Mathematics | 4 | 8% |
| Engineering | 3 | 6% |
| Nursing and Health Professions | 2 | 4% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 4% |
| Other | 9 | 19% |
| Unknown | 11 | 23% |
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 01 August 2013.
All research outputs
#18,342,133
of 22,715,151 outputs
Outputs from BMC Medical Research Methodology
#1,728
of 2,003 outputs
Outputs of similar age
#148,270
of 197,887 outputs
Outputs of similar age from BMC Medical Research Methodology
#18
of 22 outputs
Altmetric has tracked 22,715,151 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,003 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 6th percentile – i.e., 6% 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 197,887 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.