A flexible two-dimensional mortality model for use in indirect estimation

Abstract

Mortality estimates for many populations are derived using model life tables, which describe typical age patterns of human mortality. We propose a new system of model life tables as a means of improving the quality and transparency of such estimates. A flexible two-dimensional model was fitted to a collection of life tables from the Human Mortality Database. The model can be used to estimate full life tables given one or two pieces of information: child mortality only, or child and adult mortality. Using life tables from a variety of sources, we have compared the performance of new and old methods. The new model outperforms the Coale-Demeny and UN model life tables. Estimation errors are similar to those produced by the modified Brass logit procedure. The proposed model is better suited to the practical needs of mortality estimation, since both input parameters are continuous yet the second one is optional.

Assessments of mortality at oldest-old ages by province in China's 2000 and 2010 censuses

“…Additional research is needed to further understand how to assess the underestimation and how to obtain factors for adjustment. In estimating mortality at old and oldest-old ages, the Brass relational logit system (Brass, 1971), the modified logit system for linking to a model or a standard life table (Murray, Ferguson, Lopez et al, 2003), or flexible two-dimensional mortality model (Wilmoth, Zureick, Canudas-Romo et al, 2012) can be used to estimate age-specific mortality if accuracy in the selected mortality indicators in the linking function of the relational logit system can be ensured.…”

“…The purpose of the relational logit system is to find a regression-based relationship between a study population and a standard mortality scheme (normally from a model life table or a scheme based on reliable data) by linking some reliable logit-transformed mortality indicators (normally two of three indicators: infant/child mortality, adult mortality, or life expectancy) of the study population with the corresponding indicators in a standard scheme (see Murray, Ferguson, Lopez et al, 2003;Rob, 2013;Wilmoth, Zureick, Canudas-Romo et al, 2012).…”

Estimating age- and sex-specific mortality rates for small areas with TOPALS regression: an application to Brazil in 2010

“…Like all relational models (e.g. BRASS, 1971;MURRAY et al, 2003;WILMOTH et al, 2012), TOPALS builds complete schedules of age-specific rates via mathematical adjustments to a specified standard schedule. Our version of TOPALS constructs a fitted schedule of log mortality rates at ages 0…99 by adding a linear spline function with seven parameters (α 0 ... α 1 ) to a pre-specified standard schedule.…”

Regional Disparities in Brazilian Adult Mortality: an analysis using Modal Age at Death (M) and Compression of Mortality (IQR)

“…In the developing context, however, we know little about those processes (GONZAGA & COSTA, 2016;GONZAGA et al 2017;WILMOTH et al, 2012).…”

“…Part of the challenges posted to analyze the evolution of mortality indicators in such countries is related to the poor data quality (HILL, 2017;WILMOTH et al, 2012), especially in countries with great regional heterogeneity in socioeconomic and demographic indicators. In recent decades, most countries in Latin America, and especially in Brazil, experienced an accelerated decline in infant, child and adult mortality.…”