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Expectation of life at old age: revisiting Horiuchi-Coale and reconciling with Mitra

Overview of attention for article published in Genus, February 2018
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  • Good Attention Score compared to outputs of the same age (72nd percentile)

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Title
Expectation of life at old age: revisiting Horiuchi-Coale and reconciling with Mitra
Published in
Genus, February 2018
DOI 10.1186/s41118-018-0029-7
Pubmed ID
Authors

Dalkhat M. Ediev

Abstract

Data quality issues at advanced old age, such as incompleteness of registration of vital events and age misreporting, compromise estimates of the death rates and remaining life expectancy at those ages. Following up on Horiuchi and Coale (Population Studies 36: 317-326, 1982), Mitra (Population Studies 38: 313-319, 1984, Population Studies 39: 511-512, 1985), and Coale (Population Studies 39: 507-509, 1985), we examine the conventional approaches to constructing life tables from data deficient at advanced ages and the two adjustment methods by the mentioned authors. Contrary to earlier reports by Horiuchi, Coale, and Mitra, we show that the two methods are consistent and useful in drastically reducing the estimation errors in life expectancy as compared to the conventional approaches, i.e., the classical open age interval model and extrapolation of the death rates. Our results suggest complementing the classical estimates of life expectancy by adjustments using Horiuchi-Coale, Mitra, or other appropriate methods and avoiding the extrapolation method as a tool for estimating the life expectancy.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 22%
Researcher 2 22%
Professor 1 11%
Student > Bachelor 1 11%
Professor > Associate Professor 1 11%
Other 0 0%
Unknown 2 22%
Readers by discipline Count As %
Social Sciences 3 33%
Mathematics 1 11%
Agricultural and Biological Sciences 1 11%
Business, Management and Accounting 1 11%
Unknown 3 33%
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 12 February 2018.
All research outputs
#6,584,322
of 25,416,581 outputs
Outputs from Genus
#92
of 176 outputs
Outputs of similar age
#122,572
of 446,884 outputs
Outputs of similar age from Genus
#2
of 4 outputs
Altmetric has tracked 25,416,581 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 176 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.9. This one is in the 48th percentile – i.e., 48% of its peers scored the same or lower than it.
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 446,884 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 72% of its contemporaries.
We're also able to compare this research output to 4 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.