Comparing non-parametric methods for ungrouping coarsely aggregated age-specific distributions

Publikation: Konferencebidrag uden forlag/tidsskriftKonferenceabstrakt til konferenceForskningpeer review

124 Downloads (Pure)

Resumé

Demographers have often access to vital statistics that are less than ideal for the purpose of their research. In many instances demographic data are reported in coarse histograms, where the values given are only the summation of true latent values, thereby making detailed analysis troublesome. One example are abridged life tables, where data are typically summarized in 5-years age classes with an open ended interval starting at the age of 85. With increasing longevity this age structure becomes inappropriate: precious information about nonagenarians and centenarians is covered in the tail area of the age-specific distribution. Therefore it is often useful to estimate age-specific distributions by single-year of age from aggregated data. Flexible non-parametric techniques often used for this purpose are spline interpolation methods (Smith et al., 2004; Wilmoth et al., 2007; Jasilioniene et al., 2015). Recently a novel non-parametric method, based on the composite link model with a penalized likelihood, has been proposed (Rizzi et al., 2015). Here we aim to examine the performance of these different ungrouping methods in an empirical application with particular focus on the open-ended last interval. To do so we compare original NORDCAN data by single-year of age with the estimated distributions resulting from the models. We show that the penalized composite link model outperforms spline interpolation methods in presence of wide open-ended intervals.
OriginalsprogEngelsk
Publikationsdato2016
Antal sider1
StatusUdgivet - 2016

Fingeraftryk

interpolation
life table
histogram
age class
age structure
distribution
method
analysis
statistics

Citer dette

@conference{a21a9125484744fba0553b65f3155751,
title = "Comparing non-parametric methods for ungrouping coarsely aggregated age-specific distributions",
abstract = "Demographers have often access to vital statistics that are less than ideal for the purpose of their research. In many instances demographic data are reported in coarse histograms, where the values given are only the summation of true latent values, thereby making detailed analysis troublesome. One example are abridged life tables, where data are typically summarized in 5-years age classes with an open ended interval starting at the age of 85. With increasing longevity this age structure becomes inappropriate: precious information about nonagenarians and centenarians is covered in the tail area of the age-specific distribution. Therefore it is often useful to estimate age-specific distributions by single-year of age from aggregated data. Flexible non-parametric techniques often used for this purpose are spline interpolation methods (Smith et al., 2004; Wilmoth et al., 2007; Jasilioniene et al., 2015). Recently a novel non-parametric method, based on the composite link model with a penalized likelihood, has been proposed (Rizzi et al., 2015). Here we aim to examine the performance of these different ungrouping methods in an empirical application with particular focus on the open-ended last interval. To do so we compare original NORDCAN data by single-year of age with the estimated distributions resulting from the models. We show that the penalized composite link model outperforms spline interpolation methods in presence of wide open-ended intervals.",
author = "Silvia Rizzi and Mikael Thinggaard and Vaupel, {James W.} and Rune Jacobsen",
year = "2016",
language = "English",

}

Comparing non-parametric methods for ungrouping coarsely aggregated age-specific distributions. / Rizzi, Silvia; Thinggaard, Mikael; Vaupel, James W. ; Jacobsen, Rune.

2016.

Publikation: Konferencebidrag uden forlag/tidsskriftKonferenceabstrakt til konferenceForskningpeer review

TY - ABST

T1 - Comparing non-parametric methods for ungrouping coarsely aggregated age-specific distributions

AU - Rizzi, Silvia

AU - Thinggaard, Mikael

AU - Vaupel, James W.

AU - Jacobsen, Rune

PY - 2016

Y1 - 2016

N2 - Demographers have often access to vital statistics that are less than ideal for the purpose of their research. In many instances demographic data are reported in coarse histograms, where the values given are only the summation of true latent values, thereby making detailed analysis troublesome. One example are abridged life tables, where data are typically summarized in 5-years age classes with an open ended interval starting at the age of 85. With increasing longevity this age structure becomes inappropriate: precious information about nonagenarians and centenarians is covered in the tail area of the age-specific distribution. Therefore it is often useful to estimate age-specific distributions by single-year of age from aggregated data. Flexible non-parametric techniques often used for this purpose are spline interpolation methods (Smith et al., 2004; Wilmoth et al., 2007; Jasilioniene et al., 2015). Recently a novel non-parametric method, based on the composite link model with a penalized likelihood, has been proposed (Rizzi et al., 2015). Here we aim to examine the performance of these different ungrouping methods in an empirical application with particular focus on the open-ended last interval. To do so we compare original NORDCAN data by single-year of age with the estimated distributions resulting from the models. We show that the penalized composite link model outperforms spline interpolation methods in presence of wide open-ended intervals.

AB - Demographers have often access to vital statistics that are less than ideal for the purpose of their research. In many instances demographic data are reported in coarse histograms, where the values given are only the summation of true latent values, thereby making detailed analysis troublesome. One example are abridged life tables, where data are typically summarized in 5-years age classes with an open ended interval starting at the age of 85. With increasing longevity this age structure becomes inappropriate: precious information about nonagenarians and centenarians is covered in the tail area of the age-specific distribution. Therefore it is often useful to estimate age-specific distributions by single-year of age from aggregated data. Flexible non-parametric techniques often used for this purpose are spline interpolation methods (Smith et al., 2004; Wilmoth et al., 2007; Jasilioniene et al., 2015). Recently a novel non-parametric method, based on the composite link model with a penalized likelihood, has been proposed (Rizzi et al., 2015). Here we aim to examine the performance of these different ungrouping methods in an empirical application with particular focus on the open-ended last interval. To do so we compare original NORDCAN data by single-year of age with the estimated distributions resulting from the models. We show that the penalized composite link model outperforms spline interpolation methods in presence of wide open-ended intervals.

M3 - Conference abstract for conference

ER -