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Performance of the Tariff Method: validation of a simple additive algorithm for analysis of verbal autopsies

Overview of attention for article published in Population Health Metrics, August 2011
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (74th percentile)

Mentioned by

policy
1 policy source
twitter
2 tweeters

Citations

dimensions_citation
58 Dimensions

Readers on

mendeley
54 Mendeley
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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.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 2%
South Africa 1 2%
Unknown 52 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 22%
Student > Doctoral Student 6 11%
Student > Master 5 9%
Student > Ph. D. Student 5 9%
Student > Bachelor 5 9%
Other 15 28%
Unknown 6 11%
Readers by discipline Count As %
Medicine and Dentistry 22 41%
Social Sciences 6 11%
Agricultural and Biological Sciences 5 9%
Computer Science 5 9%
Economics, Econometrics and Finance 2 4%
Other 5 9%
Unknown 9 17%

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
#4,347,851
of 15,921,538 outputs
Outputs from Population Health Metrics
#150
of 326 outputs
Outputs of similar age
#44,453
of 172,147 outputs
Outputs of similar age from Population Health Metrics
#1
of 1 outputs
Altmetric has tracked 15,921,538 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 326 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.5. 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 172,147 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 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them