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Probabilistic mortality forecasting with varying age-specific survival improvements

Overview of attention for article published in Genus, January 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)

Mentioned by

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9 X users

Citations

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25 Dimensions

Readers on

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28 Mendeley
Title
Probabilistic mortality forecasting with varying age-specific survival improvements
Published in
Genus, January 2017
DOI 10.1186/s41118-016-0017-8
Pubmed ID
Authors

Christina Bohk-Ewald, Roland Rau

Abstract

Many mortality forecasting approaches extrapolate past trends. Their predictions of the future development can be quite precise as long as turning points and/or age-shifts of mortality decline are not present. To account even for such mortality dynamics, we propose a model that combines recently developed ideas in a single framework. It (1) uses rates of mortality improvement to model the aging of mortality decline, and it (2) optionally combines the mortality trends of multiple countries to catch anticipated turning points. We use simulation-based Bayesian inference to estimate and run this model that also provides prediction intervals to quantify forecast uncertainty. Validating mortality forecasts for British and Danish women from 1991 to 2011 suggest that our model can forecast regular and irregular mortality developments and that it can perform at least as well as other widely accepted approaches like, for instance, the Lee-Carter model or the UN Bayesian approach. Moreover, prospective mortality forecasts from 2012 to 2050 suggest gradual increases for British and Danish life expectancy at birth.

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 32%
Student > Ph. D. Student 4 14%
Student > Master 3 11%
Lecturer 2 7%
Other 2 7%
Other 4 14%
Unknown 4 14%
Readers by discipline Count As %
Mathematics 8 29%
Social Sciences 4 14%
Computer Science 4 14%
Medicine and Dentistry 2 7%
Biochemistry, Genetics and Molecular Biology 1 4%
Other 3 11%
Unknown 6 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 February 2017.
All research outputs
#6,280,625
of 25,542,788 outputs
Outputs from Genus
#88
of 176 outputs
Outputs of similar age
#106,010
of 424,570 outputs
Outputs of similar age from Genus
#3
of 3 outputs
Altmetric has tracked 25,542,788 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 176 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.0. This one has gotten more attention than average, scoring higher than 50% 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 424,570 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 75% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.