Visualizing Mortality Dynamics in the Lexis Diagram

Abstract

In recent decades, there has been a rapid development of demographic models and methods and an explosive growth in the range of applications of population analysis. This series seeks to provide a publication outlet both for high-quality textual and expository books on modern techniques of demographic analysis and for works that present exemplary applications of such techniques to various aspects of population analysis.Topics appropriate for the series include:• General demographic methods Volumes in the series are of interest to researchers, professionals, and students in demography, sociology, economics, statistics, geography and regional science, public health and health care management, epidemiology, biostatistics, actuarial science, business, and related fields.More information about this series at

Geofaceting: Aligning small-multiples for regions in a spatially meaningful way

“…There is no way to efficiently represent in one plot both absolute and relative values. Thus, the first two figures complement each other: Figure 1 uses the stacked bar plot technique to reveal the variation of young adult mortality in Mexican states over time; Figure 2 shows the dominant cause of death with a colored tile plot on a standard Lexis surface, which can be seen as a categorical version of a heatmap (Schöley and Willekens 2017;Rau et al 2018).…”

APC curvature plots: Displaying nonlinear age-period-cohort patterns on Lexis plots

“…Plots of the change in smoothed rates over age/cohort, over period/cohort, and over age/period are effective tools for discerning the dynamics of demographic phenomena over time, and for uncovering patterns of systematic divergence from APC linear trends. Indicative Lexis diagrams (Willets 2004) and colored Lexis surfaces (Rau et al 2008(Rau et al , 2018Richards, Kirkby, and Currie 2006) of these derivatives have been proposed as visualization techniques that could be applied to identify the presence of such patterns in Lexis plots.…”

“…Raw derivatives in vital rates are generally noisy, particularly when using highresolution data or low-frequency events. Thus, it has been suggested that the underlying data should be smoothed over ages and years in order to reduce random fluctuations 4 (Rau et al 2018); as shown in Figure 1. Figure 3 depicts Lexis surfaces of rates of mortality change over age/cohort (Panel a) and over period/cohort (Panel b) from drug-related causes in Hispanic males in the United States.…”

The Canadian Forces Cancer and Mortality Study II: a longitudinal record-linkage study protocol

“…CMAJ OPEN, 6(4) E623 • Lexis diagrams: 13 0 Present incidence data where age-period-cohort effects are likely to influence mortality rates over a long followup period. 0 Particularly useful in visually communicating temporal and population subset differences in incidence.…”