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Hierarchical Bayesian model

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Journal Article
Demography (2013) 50 (6): 2053–2073.
Published: 01 August 2013
.... We used linked census-mortality information for 25- to 74-year-olds in the 2001 census followed for up to three years. Hierarchical Bayesian modeling provided a means of handling sparse data. Posterior mortality rates were directly age-standardized. We found little evidence of mortality differences...
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Published: 01 August 2013
Fig. 1 Observed gender-averaged Pacific mean mortality rates ( × 100,000) and posterior estimates of the shrinkage parameter and structural mean rates from the hierarchical Bayesian model. The lines were computed using spline interpolation between computed gender-averaged posterior means More
Journal Article
Demography (2024) 61 (2): 439–462.
Published: 01 April 2024
... to obtain. I present a Bayesian hierarchical model framework for prediction of mortality rates at a small or subnational level. By combining ideas from demography and epidemiology, the classical mortality modeling framework is extended to include an additional spatial component capturing regional...
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Includes: Supplementary data
Journal Article
Demography (2022) 59 (5): 1713–1737.
Published: 01 October 2022
... ), and migration ( Bijak 2008 ). In terms of estimating the full demographic accounting identity, Wheldon et al. (2013) proposed a method for the reconstruction of past populations. The model embeds the demographic accounting equation within a Bayesian hierarchical framework, using information from available...
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Includes: Supplementary data
Journal Article
Demography (2011) 48 (3): 815–839.
Published: 12 July 2011
... fall below replacement level. It models the decline in TFR as the sum of two logistic functions that depend on the current TFR level, and a random term. A Bayesian hierarchical model is used to project future TFR based on both the country’s TFR history and the pattern of all countries. It is estimated...
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Includes: Supplementary data
Journal Article
Demography (2017) 54 (6): 2025–2041.
Published: 10 October 2017
... in death counts is relatively high, and thus the underlying mortality levels are unclear. We present a Bayesian hierarchical model to estimate mortality at the subnational level. The model builds on characteristic age patterns in mortality curves, which are constructed using principal components from a set...
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Journal Article
Demography (2013) 50 (3): 777–801.
Published: 15 March 2013
...Adrian E. Raftery; Jennifer L. Chunn; Patrick Gerland; Hana Ševčíková Abstract We propose a Bayesian hierarchical model for producing probabilistic forecasts of male period life expectancy at birth for all the countries of the world to 2100. Such forecasts would be an input to the production...
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Includes: Supplementary data
Journal Article
Demography (2020) 57 (3): 1171–1192.
Published: 09 June 2020
... problems. We use a Bayesian hierarchical time-series model that allows us to integrate the parish-level data set and prior population information in a coherent manner. The procedure provides us with model-based posterior intervals for the final population estimates. We demonstrate its applicability...
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Includes: Supplementary data
Journal Article
Demography (2015) 52 (3): 1035–1059.
Published: 12 May 2015
... ; Rogers et al. 1978 ), relational models (Brass 1974 ), functional models (De Beer 2011 ; Hyndman and Booth 2008 ; Hyndman and Ullah 2007 ; Lee and Carter 1992 ), and hierarchical Bayesian models (Czado et al. 2005 ; Girosi and King 2008 ). Of these, the most successful and widely used...
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Journal Article
Demography (2015) 52 (5): 1627–1650.
Published: 10 September 2015
... appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Autoregressive model Bayesian hierarchical model Markov chain Monte Carlo World population prospects In this article we propose a method...
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Journal Article
Demography (2023) 60 (3): 915–937.
Published: 01 June 2023
... projections have been probabilistic, based on Bayesian hierarchical models for fertility and mortality ( Raftery, Alkema et al. 2014 ; Raftery et al. 2012 ; United Nations 2022b ). While these methods have been extended to include probabilistic migration ( Azose and Raftery 2015 ; Azose et al. 2016...
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Includes: Supplementary data
Journal Article
Demography (2013) 50 (6): 1981–1984.
Published: 17 October 2013
... and Wolfinger ( 2001 ) on this point.) More specifically, it is especially important to understand that for Bayesian hierarchical APC models, the exchangeability on any one or more of A, P, or C turns a linear model into a nonlinear one. The same is true of introducing random effects instead of fixed effects...
Journal Article
Demography (2014) 51 (5): 1933–1954.
Published: 15 August 2014
... functional principal components models of simple functions of the rates. Booth et al. ( 2006 ) and Shang et al. ( 2011 ) discussed interesting comparisons and evaluations of some of these methods for mortality forecasting. Also, Bayesian hierarchical time series models have been proposed to derive fertility...
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Journal Article
Demography (2013) 50 (6): 1969–1971.
Published: 17 October 2013
... Yang Y. ( 2006 ). Bayesian inference for hierarchical age-period-cohort models of repeated cross-section survey data . Sociological Methodology , 36 , 39 – 74 . 10.1111/j.1467-9531.2006.00174.x Yang Y. ( 2008 ). Trends in U.S. adult chronic disease mortality: Age, period...
Journal Article
Demography (2005) 42 (3): 537–558.
Published: 01 August 2005
.... “Empirical Bayes Estimation of Small Area Adult Mortality Risk in Addis Ababa, Ethiopia.” Paper presented at the 2004 meeting of the Population Association of America, Boston. Fisher, R. and J. Asher. 2000. “Bayesian Hierarchical Modeling of U.S. County Poverty Rates.” Paper presented at the 2000 meeting...
Journal Article
Demography (2012) 49 (3): 773–796.
Published: 23 June 2012
... carried out a sensitivity analysis in R using alternative estimation algorithms applicable to this class of problems, including maximum marginal likelihood (using both Laplacian and Gaussian-Quadrature methods) and hierarchical Bayesian models estimated using Markov Chain Monte Carlo (MCMC) under a Gibbs...
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Journal Article
Demography (2015) 52 (6): 1995–2019.
Published: 20 October 2015
... based on small absolute counts. Bayesian MCMC estimation of a log-normal Poisson model allows the calculation of the variance estimates of the degree of segregation in a single overall model, and credible intervals are obtained to provide a measure of uncertainty around those estimates. The procedure...
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Journal Article
Demography (2014) 51 (3): 811–834.
Published: 25 April 2014
... continuous variables at individual-, household-, and neighborhood-level are standardized into z scores to facilitate the Bayesian statistical computation. We employ multilevel spatial Poisson models that incorporate both the standard neighborhood random effects and the spatially correlated random...
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Journal Article
Demography (2018) 55 (4): 1363–1388.
Published: 05 July 2018
... like Brazil. Statisticians have also addressed estimation in cases of incomplete or underreported data. Raftery ( 1988 ) proposed a Bayesian approach to the general problem of inferring the number of binomial trials from the number of successes. Moreno and Girón ( 1998 ) developed a model...
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Journal Article
Demography (2021) 58 (6): 2193–2218.
Published: 01 December 2021
... of the LFS and Facebook data, paying particular attention to the biases of these sources. The results indicate visible yet uncertain differences between model estimates using the Bayesian framework and individual sources. Sensitivity analysis techniques are used to evaluate the quality of the model...
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Includes: Supplementary data