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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Evaluating bias due to data linkage error in electronic healthcare records
|
|---|---|
| Published in |
BMC Medical Research Methodology, March 2014
|
| DOI | 10.1186/1471-2288-14-36 |
| Pubmed ID | |
| Authors |
Katie Harron, Angie Wade, Ruth Gilbert, Berit Muller-Pebody, Harvey Goldstein |
| Abstract |
Linkage of electronic healthcare records is becoming increasingly important for research purposes. However, linkage error due to mis-recorded or missing identifiers can lead to biased results. We evaluated the impact of linkage error on estimated infection rates using two different methods for classifying links: highest-weight (HW) classification using probabilistic match weights and prior-informed imputation (PII) using match probabilities. |
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 % |
|---|---|---|
| Canada | 1 | 33% |
| Sweden | 1 | 33% |
| United States | 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 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 2% |
| United States | 1 | <1% |
| Australia | 1 | <1% |
| Unknown | 105 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 20 | 18% |
| Student > Master | 20 | 18% |
| Researcher | 19 | 17% |
| Student > Postgraduate | 7 | 6% |
| Student > Doctoral Student | 7 | 6% |
| Other | 19 | 17% |
| Unknown | 17 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 31 | 28% |
| Computer Science | 11 | 10% |
| Nursing and Health Professions | 7 | 6% |
| Social Sciences | 7 | 6% |
| Economics, Econometrics and Finance | 4 | 4% |
| Other | 20 | 18% |
| Unknown | 29 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 January 2017.
All research outputs
#5,871,514
of 22,753,345 outputs
Outputs from BMC Medical Research Methodology
#894
of 2,007 outputs
Outputs of similar age
#54,961
of 221,299 outputs
Outputs of similar age from BMC Medical Research Methodology
#15
of 32 outputs
Altmetric has tracked 22,753,345 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 2,007 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one has gotten more attention than average, scoring higher than 55% 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 221,299 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 32 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 53% of its contemporaries.