2019
DOI: 10.4054/demres.2019.41.42
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APC curvature plots: Displaying nonlinear age-period-cohort patterns on Lexis plots

Abstract: access work is published under the terms of the Creative Commons Attribution 3.0 Germany (CC BY 3.0 DE), which permits use, reproduction, and distribution in any medium, provided the original author(s) and source https://creativecommons.org/licenses/by/3.0/de/legalcode DEMOGRAPHIC RESEARCH , ARTICLE NOVEMBER raphic-research.org/Volumes/

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Cited by 9 publications
(10 citation statements)
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“…Lexis fields offer a new way to summarize multiple Lexis surfaces in a single surface. Other strategies include the composite surfaces of Schöley and Willekens (2017) and the APC curvature plots of Acosta and van Raalte (2019). Small multiples of Lexis surfaces (for example, panel plots of Lexis surfaces), on the other hand, constitute a de-layering (e.g., Remund, Camarda, and Riffe 2018;Kashnitsky and Aburto 2019), as these are spatially disjoint.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Lexis fields offer a new way to summarize multiple Lexis surfaces in a single surface. Other strategies include the composite surfaces of Schöley and Willekens (2017) and the APC curvature plots of Acosta and van Raalte (2019). Small multiples of Lexis surfaces (for example, panel plots of Lexis surfaces), on the other hand, constitute a de-layering (e.g., Remund, Camarda, and Riffe 2018;Kashnitsky and Aburto 2019), as these are spatially disjoint.…”
Section: Discussionmentioning
confidence: 99%
“…Surfaces are often displayed as heat maps, contour maps, perspective plots, or variants of these things (Vaupel, Gambill, and Yashin 1987). Various kinds of quantities, such as raw magnitudes, differences (Minton et al 2017), excesses (Remund, Camarda, and Riffe 2018;Acosta and van Raalte 2019), ratios (Canudas-Romo and Schoen 2005), intensities, proportions, derivatives (Rau et al 2017), and even compositions (Schöley and Willekens 2017) can be displayed on Lexis surfaces to put age, period, cohort, or other patterns in relief.…”
Section: Introductionmentioning
confidence: 99%
“…The changes in the magnitude or the location of the curvatures by cause over time could help us determine whether the cohort disadvantage resulted from a sequence of temporary age-period interactions, or, conversely, from a process that operated continuously throughout the life course of the boomers. To analyze these temporal dynamics, we constructed APC curvature plots (Acosta and van Raalte 2019). This graphical tool allowed us to display the changes in the nonlinear APC components over time on a Lexis diagram by focusing on the ridges; i.e., the series of Lexis coordinates in which the relative risk reaches a maximum.…”
Section: Dynamics Of the Cohorts' Excess Mortality Over Timementioning
confidence: 99%
“…With regard to the methods used to analyze the temporal pattern of the disadvantage in mortality, there is more than one approach to detecting excess mortality (Acosta and van Raalte 2019). Because each approach is conceptually different, their application can lead to different estimations.…”
Section: Limits Of the Analytical Strategy And Suggestions For Futurementioning
confidence: 99%
“…Acosta and van Raalte (2019): APC curvature plots: Displaying nonlinear ageperiod-cohort patterns onLexis plots  Cimentada, Klüsener, and Riffe (2020): Exploring the demographic history of populations with enhanced Lexis surfaces  Kashnitsky and Aburto (2019): Geofaceting: Aligning small multiples for regions in a spatially meaningful way  Nowok (2020): A visual tool to explore the composition of international migration flows in EU countries, 1998-2015  Pattaro, Vanderbloemen, and Minton (2020): Visualizing fertility trends for 45 countries using composite lattice plots  Riffe and Aburto (2020): Lexis fields  Schöley (2021): The centered ternary balance scheme: A technique to visualize surfaces of unbalanced three-part compositions Acosta and van Raalte (2019) use a Lexis representation to visualize curvatures, the estimable nonlinear component of age, period, and cohort effects. The visualization technique captures and simplifies key features from several Lexis surfaces and displays them on a single surface, thereby enabling comparisons across surfaces.…”
mentioning
confidence: 99%