You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Addressing missing values in routine health information system data: an evaluation of imputation methods using data from the Democratic Republic of the Congo during the COVID-19 pandemic
|
|---|---|
| Published in |
Population Health Metrics, November 2021
|
| DOI | 10.1186/s12963-021-00274-z |
| Pubmed ID | |
| Authors |
Shuo Feng, Celestin Hategeka, Karen Ann Grépin |
X Demographics
The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 22% |
| United Kingdom | 2 | 22% |
| Spain | 1 | 11% |
| Senegal | 1 | 11% |
| Hong Kong | 1 | 11% |
| Unknown | 2 | 22% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 78% |
| Scientists | 2 | 22% |
Mendeley readers
The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 53 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 5 | 9% |
| Researcher | 4 | 8% |
| Lecturer | 3 | 6% |
| Student > Doctoral Student | 3 | 6% |
| Student > Ph. D. Student | 3 | 6% |
| Other | 7 | 13% |
| Unknown | 28 | 53% |
| Readers by discipline | Count | As % |
|---|---|---|
| Social Sciences | 6 | 11% |
| Computer Science | 4 | 8% |
| Medicine and Dentistry | 3 | 6% |
| Business, Management and Accounting | 2 | 4% |
| Agricultural and Biological Sciences | 2 | 4% |
| Other | 7 | 13% |
| Unknown | 29 | 55% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 13 February 2022.
All research outputs
#4,106,035
of 25,287,709 outputs
Outputs from Population Health Metrics
#103
of 414 outputs
Outputs of similar age
#83,995
of 436,717 outputs
Outputs of similar age from Population Health Metrics
#4
of 6 outputs
Altmetric has tracked 25,287,709 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 414 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.6. This one has done well, scoring higher than 75% 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 436,717 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 80% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.