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            Visualizing Mortality Dynamics in the Lexis Diagram

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            Author(s)
            Rau, Roland
            Bohk-Ewald, Christina
            Muszyńska, Magdalena M.
            Vaupel, James W.
            Contributor(s)
            Land, Kenneth (editor)
            Collection
            European Research Council (ERC)
            Language
            English
            Show full item record
            Abstract
            The goal of this book is simple: We would like to show how mortality dynamics can be visualized in the so-called Lexis diagram. To appeal to as many potential readers as possible, we do not require any specialist knowledge. This approach may be disappointing: Demographers may have liked more information about the mathematical underpinnings of population dynamics on the Lexis surface as demonstrated, for instance, by Arthur and Vaupel in 1984. Statisticians would have probably preferred more information about the underlying smoothing methods that were used. Epidemiologists likewise might miss discussions about the etiology of diseases. Sociologists would have probably expected that our results were more embedded into theoretical frameworks....
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/195001
            Keywords
            data; lexis diagram; mortality dynamics; software; Breast cancer; Colorectal cancer; Creative Commons license; Human Mortality Database; Life expectancy; Lung cancer; Seasonality; United States; thema EDItEUR::U Computing and Information Technology
            DOI
            10.1007/978-3-319-64820-0
            ISBN
            9783319648200
            Publisher
            Springer Nature
            Publisher website
            http://www.springernature.com/oabooks
            Publication date and place
            Cham, 2018
            Grantor
            • FP7 Ideas: European Research Council
            Series
            The Springer Series on Demographic Methods and Population Analysis,
            Pages
            175
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            • logo EUEuropean Union
              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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