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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Performance of the Tariff Method: validation of a simple additive algorithm for analysis of verbal autopsies
|
|---|---|
| Published in |
Population Health Metrics, August 2011
|
| DOI | 10.1186/1478-7954-9-31 |
| Pubmed ID | |
| Authors |
Spencer L James, Abraham D Flaxman, Christopher JL Murray |
| Abstract |
Verbal autopsies provide valuable information for studying mortality patterns in populations that lack reliable vital registration data. Methods for transforming verbal autopsy results into meaningful information for health workers and policymakers, however, are often costly or complicated to use. We present a simple additive algorithm, the Tariff Method (termed Tariff), which can be used for assigning individual cause of death and for determining cause-specific mortality fractions (CSMFs) from verbal autopsy data. |
X Demographics
The data shown below were collected from the profiles of 2 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 | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 1% |
| South Africa | 1 | 1% |
| Unknown | 67 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 16% |
| Student > Master | 9 | 13% |
| Student > Ph. D. Student | 7 | 10% |
| Student > Doctoral Student | 7 | 10% |
| Student > Postgraduate | 4 | 6% |
| Other | 20 | 29% |
| Unknown | 11 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 22 | 32% |
| Computer Science | 8 | 12% |
| Social Sciences | 6 | 9% |
| Agricultural and Biological Sciences | 6 | 9% |
| Nursing and Health Professions | 4 | 6% |
| Other | 9 | 13% |
| Unknown | 14 | 20% |
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 14 November 2018.
All research outputs
#6,213,431
of 22,725,280 outputs
Outputs from Population Health Metrics
#182
of 392 outputs
Outputs of similar age
#34,927
of 119,775 outputs
Outputs of similar age from Population Health Metrics
#4
of 19 outputs
Altmetric has tracked 22,725,280 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 392 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.7. This one has gotten more attention than average, scoring higher than 53% 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 119,775 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 70% of its contemporaries.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.