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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The probability of being identified as an outlier with commonly used funnel plot control limits for the standardised mortality ratio
|
|---|---|
| Published in |
BMC Medical Research Methodology, July 2012
|
| DOI | 10.1186/1471-2288-12-98 |
| Pubmed ID | |
| Authors |
Sarah E Seaton, Bradley N Manktelow |
| Abstract |
Emphasis is increasingly being placed on the monitoring of clinical outcomes for health care providers. Funnel plots have become an increasingly popular graphical methodology used to identify potential outliers. It is assumed that a provider only displaying expected random variation (i.e. 'in-control') will fall outside a control limit with a known probability. In reality, the discrete count nature of these data, and the differing methods, can lead to true probabilities quite different from the nominal value. This paper investigates the true probability of an 'in control' provider falling outside control limits for the Standardised Mortality Ratio (SMR). |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Mexico | 1 | 33% |
| United Kingdom | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 3% |
| United States | 1 | 3% |
| Sweden | 1 | 3% |
| Switzerland | 1 | 3% |
| Unknown | 28 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 31% |
| Student > Ph. D. Student | 6 | 19% |
| Professor | 3 | 9% |
| Lecturer | 2 | 6% |
| Professor > Associate Professor | 2 | 6% |
| Other | 2 | 6% |
| Unknown | 7 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 12 | 38% |
| Mathematics | 7 | 22% |
| Psychology | 1 | 3% |
| Nursing and Health Professions | 1 | 3% |
| Social Sciences | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 9 | 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 14 July 2017.
All research outputs
#13,380,136
of 22,701,287 outputs
Outputs from BMC Medical Research Methodology
#1,278
of 2,002 outputs
Outputs of similar age
#90,560
of 163,504 outputs
Outputs of similar age from BMC Medical Research Methodology
#17
of 35 outputs
Altmetric has tracked 22,701,287 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,002 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 33rd percentile – i.e., 33% 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 163,504 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.