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A unified framework of demographic time

Demographic thought and practice is largely conditioned by the Lexis diagram, a two-dimensional graphical representation of the identity between age, period, and birth cohort. This relationship does not account for remaining years of life, total length of life, or time of death, whose use in demogra...

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Detalles Bibliográficos
Autores principales: Riffe, Tim, Schöley, Jonas, Villavicencio, Francisco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5569647/
https://www.ncbi.nlm.nih.gov/pubmed/28890551
http://dx.doi.org/10.1186/s41118-017-0024-4
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author Riffe, Tim
Schöley, Jonas
Villavicencio, Francisco
author_facet Riffe, Tim
Schöley, Jonas
Villavicencio, Francisco
author_sort Riffe, Tim
collection PubMed
description Demographic thought and practice is largely conditioned by the Lexis diagram, a two-dimensional graphical representation of the identity between age, period, and birth cohort. This relationship does not account for remaining years of life, total length of life, or time of death, whose use in demographic research is both underrepresented and incompletely situated. We describe an identity between these six demographic time measures and describe the sub-identities and diagrams that pertain to this identity. We provide an application of this framework to the measurement of late-life morbidity prevalence. We generalize these relationships to higher order identities derived from an arbitrary number of events in calendar time. Our examples are based on classic human demography, but the concepts we present can reveal patterns and relationships in any event history data, and contribute to the study of human or non-human population dynamics measured on any scale of calendar time.
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spelling pubmed-55696472017-09-07 A unified framework of demographic time Riffe, Tim Schöley, Jonas Villavicencio, Francisco Genus Original Article Demographic thought and practice is largely conditioned by the Lexis diagram, a two-dimensional graphical representation of the identity between age, period, and birth cohort. This relationship does not account for remaining years of life, total length of life, or time of death, whose use in demographic research is both underrepresented and incompletely situated. We describe an identity between these six demographic time measures and describe the sub-identities and diagrams that pertain to this identity. We provide an application of this framework to the measurement of late-life morbidity prevalence. We generalize these relationships to higher order identities derived from an arbitrary number of events in calendar time. Our examples are based on classic human demography, but the concepts we present can reveal patterns and relationships in any event history data, and contribute to the study of human or non-human population dynamics measured on any scale of calendar time. Springer International Publishing 2017-08-22 2017 /pmc/articles/PMC5569647/ /pubmed/28890551 http://dx.doi.org/10.1186/s41118-017-0024-4 Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Article
Riffe, Tim
Schöley, Jonas
Villavicencio, Francisco
A unified framework of demographic time
title A unified framework of demographic time
title_full A unified framework of demographic time
title_fullStr A unified framework of demographic time
title_full_unstemmed A unified framework of demographic time
title_short A unified framework of demographic time
title_sort unified framework of demographic time
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5569647/
https://www.ncbi.nlm.nih.gov/pubmed/28890551
http://dx.doi.org/10.1186/s41118-017-0024-4
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