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Bayesian geoadditive modelling of breastfeeding initiation in Nigeria

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  • Samson B. Adebayo

    (Department of Statistics, University of Munich, Germany)

Abstract

A study into the geographical variability of timing of initial child breastfeeding after birth was carried out with the data set from the 1999 Nigeria Demographic and Health Survey. The effect of the metrical covariate of the mother's age at birth was assumed to be nonlinear and estimated nonparametrically. Other categorical covariates are estimated in the usual parametric form. Within a Bayesian context, appropriate priors are assigned for the geographical location, vector of the unknown (nonlinear) smooth functions and a further vector of the fixed effect parameters. For instance, a Markov random field prior is assumed on the spatial effects. Inferences are based on Markov chain Monte Carlo techniques while Bayesian model diagnostics are based on the deviance information criteria. Copyright © 2004 John Wiley & Sons, Ltd.

Suggested Citation

  • Samson B. Adebayo, 2004. "Bayesian geoadditive modelling of breastfeeding initiation in Nigeria," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(2), pages 267-281.
    • Handle: RePEc:jae:japmet:v:19:y:2004:i:2:p:267-281
    DOI: 10.1002/jae.732
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    References listed on IDEAS

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    Cited by:

    1. Ezra Gayawan & Samson B. Adebayo, 2013. "A Bayesian semiparametric multilevel survival modelling of age at first birth in Nigeria," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 28(45), pages 1339-1372.

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