Quality and Quantity

, Volume 40, Issue 6, pp 935–957 | Cite as

A Geo-Additive Bayesian Discrete-Time Survival Model and its Application to Spatial Analysis of Childhood Mortality in Malawi

Abstract

We describe a flexible geo-additive Bayesian survival model that controls, simultaneously, for spatial dependence and possible nonlinear or time-varying effects of other variables. Inference is fully Bayesian and is based on recently developed Markov Chain Monte Carlo techniques. In illustrating the model we introduce a spatial dimension in modelling under-five mortality among Malawian children using data from Malawi Demographic and Health Survey of 2000. The results show that district-level socioeconomic characteristics are important determinants of childhood mortality. More importantly, a separate spatial process produces district clustering of childhood mortality indicating the importance of spatial effects. The visual nature of the maps presented in this paper highlights relationships that would, otherwise, be overlooked in standard methods.

Keywords

Bayesian inference discrete-time survival models geo-additive models Markov Chain Monte Carlo (MCMC) Spatial modelling time-varying effects under-five mortality 

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Copyright information

© Springer 2006

Authors and Affiliations

  1. 1.Clinical Sciences Research Institute, CSB, UHCW CampusWarwick Medical SchoolCoventryUK
  2. 2.Department of StatisticsStockholm UniversityStockholmSweden

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