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Activity Number: 27 - SDNS Speed Session
Type: Contributed
Date/Time: Sunday, August 8, 2021 : 1:30 PM to 3:20 PM
Sponsor: Social Statistics Section
Abstract #317872
Title: Sex Ratio of Mortality Rate Estimation Using a Bayesian Modeling Approach
Author(s): Fengqing Chao* and Bruno Masquelier and Haavard Rue and Hernando Ombao and Leontine Alkema
Companies: King Abdullah University of Science and Technology and Universite catholique de Louvain and King Abdullah University of Science and Technology and King Abdullah University of Science and Technology and University of Massachusetts, Amherst
Keywords: Bayesian hierarchical model; time series; Integrated Nested Laplace Approximations; sex-specific mortality

Producing accurate estimates of sex ratio of mortality rate is essential in understanding population structure and dynamics. We introduce a Bayesian hierarchical model to estimate the disparity in child and adolescent mortality by sex for all countries over time. The Bayesian model synthesizes data with varying levels, trends and associated uncertainties. The hierarchical modeling structure allows information exchange between data-saturated country-periods and data-poor ones to assist estimation in country-periods lack of observations. We model the global expected sex ratio using all the observations with a random walk model of order 2 (RW2). The RW2 is flexible to capture the non-linear global trend and is computationally efficient relative to splines model. The model can be used to estimate sex disparity in mortality for broader age groups below age 25. We conclude that the Bayesian model is an efficient and robust approach for sex ratio of mortality estimation.

Authors who are presenting talks have a * after their name.

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