Perturbation Analysis of Indices of Lifespan Variability.
A number of indices exist to calculate lifespan variation, each with different underlying properties. Here, we present new formulae for the response of seven of these indices to changes in the underlying mortality schedule (life disparity, Gini coefficient, standard deviation, variance, Theil's inde...
| Publicado en: | Demography (Springer Nature) Vol. 50; no. 5; pp. 1615 - 1641 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Oct2013
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=90429086&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 90429086 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00703370 DEM jtl: Demography (Springer Nature) issn: 00703370 maglogo: N pubinfo: dt: Oct2013 vid: 50 iid: 5 pid: 237 pub: Springer Nature artinfo: ui: 90429086 10.1007/s13524-013-0223-3 ppf: 1615 ppct: 26 formats: fmt: @attributes: type: P size: 741KB tig: atl: Perturbation Analysis of Indices of Lifespan Variability. aug: au: Raalte, Alyson Caswell, Hal affil: Max Planck Institute for Demographic Research, Konrad-Zuse Str. 1 18057 Rostock Germany Biology Department MS-34, Woods Hole Oceanographic Institution, Woods Hole 02543 USA su: Perturbation theory Mathematical models of life expectancy Mathematical decomposition Mortality -- Mathematical models Markov processes sug: subj: Perturbation theory Mathematical models of life expectancy Mathematical decomposition Mortality -- Mathematical models Markov processes ab: A number of indices exist to calculate lifespan variation, each with different underlying properties. Here, we present new formulae for the response of seven of these indices to changes in the underlying mortality schedule (life disparity, Gini coefficient, standard deviation, variance, Theil's index, mean logarithmic deviation, and interquartile range). We derive each of these indices from an absorbing Markov chain formulation of the life table, and use matrix calculus to obtain the sensitivity and the elasticity (i.e., the proportional sensitivity) to changes in age-specific mortality. Using empirical French and Russian male data, we compare the underlying sensitivities to mortality change under different mortality regimes to determine the conditions under which the indices might differ in their conclusions about the magnitude of lifespan variation. Finally, we demonstrate how the sensitivities can be used to decompose temporal changes in the indices into contributions of age-specific mortality changes. The result is an easily computable method for calculating the properties of this important class of longevity indices. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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