How much can we trust life tables? Sensitivity of mortality measures to right-censoring treatment
Palgrave Communications, 2:15049 (2016)
International organizations, research institutions, insurance companies, pension funds, and health policy makers calculate human mortality measures from life tables. Life-table data, though, are usually right-censored and mortality measures are sensitive to the way censoring is addressed. In this article we propose fitting a parametric model that describes well human mortality patterns, the gamma-Gompertz-Makeham, accounting for censoring, and constructing model-based equivalents of five mortality measures: life expectancy, the modal age at death, life disparity, entropy, and the Gini coefficient. We show that, in comparison to life-table measures, model-based measures are less sensitive to the age at censoring and can be only slightly distorted even if the age at censoring is low. We also compare life-table and model-based mortality measures for a population with an underlying Gompertz mortality schedule in which a fixed proportion of the population is censored.
Keywords: life tables, mathematical demography, statistical analysis